Electric vehicle power management systems

ABSTRACT

A system that enables power flow management for electrical devices, such as electric vehicles. Power flow managers can coordinate charging activities. Power flow decisions may be based on site-level information. Power flow management strategies may be optimized. Power spikes may be avoided by using safe failure modes. Generation stacks may be used for reducing cost. AGC commands are used to control power resources. Power regulation are apportioned to power resources, and power regulation ranges may be determined. Power flow strategies are implemented in response to changes in intermittent power flow. Locations of devices may be determined using network fingerprints. Power flow measurements are determined, and AC power flows are inferred from DC power flows. Network traffic consumption are minimized. Communication protocols are translated. Enhanced vehicle communications are provided that communicate to vehicle subsystems, that arbitrate smart charge points, and that use existing hardware, non-specific hardware, or control extensibility systems.

This patent application is a continuation of, and incorporates herein byreference, U.S. patent application Ser. No. 14/338,427 filed Jul. 23,2014, which is a continuation of U.S. patent application Ser. No.13/671,717 filed Nov. 8, 2012, which is a continuation of each of thefollowing applications: U.S. patent application Ser. No. 12/751,853filed Mar. 31, 2010, U.S. patent application Ser. No. 12/751,837 filedMar. 31, 2010, U.S. patent application Ser. No. 12/751,821 filed Mar.31, 2010, U.S. patent application Ser. No. 12/751,845 filed Mar. 31,2010, U.S. patent application Ser. No. 12/751,862 filed Mar. 31, 2010,and U.S. patent application Ser. No. 12/751,852 filed Mar. 31, 2010,which each claim priority to U.S. Provisional Patent Application No.61/165,344 filed on Mar. 31, 2009. This application also incorporatesherein by reference the following: U.S. patent application Ser. No.12/252,657 filed Oct. 16, 2008; U.S. patent application Ser. No.12/252,209 filed Oct. 15, 2008; U.S. patent application Ser. No.12/252,803 filed Oct. 16, 2008; and U.S. patent application Ser. No.12/252,950 filed Oct. 16, 2008. Each of these applications isincorporated herein in its entirety.

This application includes material which is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

FIELD OF THE INVENTION

The present invention relates in general to the field of electricvehicles, and in particular to novel systems and methods for power flowmanagement for electric vehicles.

BACKGROUND OF THE INVENTION

Low-level electrical and communication interfaces to enable charging anddischarging of electric vehicles with respect to the grid is describedin U.S. Pat. No. 5,642,270 to Green et al., entitled, “Battery poweredelectric vehicle and electrical supply system,” incorporated herein byreference. The Green reference describes a bi-directional charging andcommunication system for grid-connected electric vehicles.

Communication parameters can be used to infer a remote machine'soperating system fingerprint. For example, in an IP over Ethernet basedsystem there are several layers of message framing all with unique orsemi unique characteristics. The MAC address of the gateway, the numberof network peers and their addresses can all be determined by watchingexisting network traffic, or by soliciting such information of thenetwork peers themselves. Techniques like port scanning are in wide usefor determining network topology. Several techniques exist fordetermining the host operating systems of network peers using IP stackfingerprinting.

Modern automobiles, including electric vehicles, have many electroniccontrol units for various subsystems. While some subsystems areindependent, communications among others are essential. To fill thisneed, controller-area network (CAN or CAN-bus) was devised as amulti-master broadcast serial bus standard for connecting electroniccontrol units. Using a message based protocol designed specifically forautomotive applications, CAN-bus is a vehicle bus standard designed toallow microcontrollers and devices to communicate with each other withina vehicle without a host computer. The CAN-bus is used in vehicles toconnect the engine control unit, transmission, airbags, antilockbraking, cruise control, audio systems, windows, doors, mirroradjustment, climate control, and seat control. CAN is one of fiveprotocols used in the (On-Board Diagnostics) OBD-II vehicle diagnosticsstandard.

Modern vehicles contain a variety of subsystems that may benefit fromcommunications with various off-vehicle entities. As the smart energymarketplace evolves, multiple application-level protocols may furtherdevelop for the control of power flow for electric vehicles and withinthe home. For example, energy management protocols are being developedfor both ZigBee and Homeplug. A vehicle manufacturer may need to supportmultiple physical communications mediums. For example, ZigBee is used insome installations while PLC is used in others. Considering the verylong service life of items such as utility meters and automobiles, theuse of multiple incompatible protocols may pose an barrier todeployment. For example, if a homeowner buys a car that utilizes oneprotocol and receives a utility meter that uses another protocol, it isunlikely that either device will quickly replace other device.

The electric power grid has become increasingly unreliable andantiquated, as evidenced by frequent large-scale power outages. Gridinstability wastes energy, both directly and indirectly, e.g. byencouraging power consumers to install inefficient forms of backupgeneration. While clean forms of energy generation, such as wind andsolar, can help to address the above problems, they suffer fromintermittency. Hence, grid operators are reluctant to rely heavily onthese sources, making it difficult to move away from carbon-intensiveforms of electricity.

With respect to the electric power grid, electric power delivered duringperiods of peak demand costs substantially more than off-peak power. Theelectric power grid contains limited inherent facility for storingelectrical energy. Electricity must be generated constantly to meetuncertain demand, which often results in over-generation (and hencewasted energy) and sometimes results in under-generation (and hencepower failures). Distributed electric resources, en masse can, inprinciple, provide a significant resource for addressing the aboveproblems. However, current power services infrastructure lacksprovisioning, and flexibility that are required for aggregating a largenumber of small-scale resources, such as electric vehicle batteries, tomeet large-scale needs of power services.

The communications protocol by which an utility controls a power plantin regulation mode is known as Automatic Generation Control, or AGC. AGCsignals have been sent to large scale conventional power plants,generally with a capacity of 1 Megawatt or more.

Modern Electric vehicles could benefit in a variety of ways from acentrally controlled smart charging program, wherein a central servercoordinates the charging activities of a number of vehicles. Significantopportunities for improvement exist in managing power flow at locallevel. More economical, reliable electrical power needs to be providedat times of peak demand. Power services, such as regulation and spinningreserves, can be provided to electricity markets to provide asignificant economic opportunity. Technologies can be enabled to providebroader use of intermittent power sources, such as wind and solar.

What is needed are power flow management systems and methods that managepower flow at the site-level, that implement various power flowstrategies for the optimizing how to dispatch the resources undermanagement, that avoid power spikes, and that minimize the total dailycost of providing energy generation. Novel grid stabilization systemsand methods are needed that aggregate the power generation behavior ofresources via Automatic Generation Control (AGC), that provide systemfrequency regulation via AGC, and that smooth and level powergeneration.

While various other techniques for fingerprinting devices on a networkare known in the art, novel methods are needed to determine the networklocation of mobile devices connected to a power grid in order to provideenhanced techniques for smart charging. Significant opportunities forimprovement exist with respect to locating electric vehicles on anetwork that communications with power grids and various mobile devices.What is needed are systems and methods that determine the location of adevice with respect to a known location on the electrical grid. Withrespect to the statistical nature of the fingerprint, there is also aneed for novel statistical modeling that weighs the relevance of variouspieces of communication based information collected to construct anetwork fingerprint. In particular, novel systems and methods are neededthat efficiently determine the network location of mobile devices onnetworks for power management systems.

Significant opportunities for improvement exist with respect to meteringand translating measurements for power grids and electric vehicles. Whatis needed are systems and methods that provide for the efficienttransfer of higher levels of information dealing with mobile populationsof electric vehicles, the complexities of accurately metering such largepopulations.

Improvement also exist with respect to communications between powergrids and electric vehicles. What is needed are systems and methods thatprovide for the complexity of translating information among variousprotocols. In addition to cost of translating messages, there is a costassociated with transmitting messages across networks. As such, there isalso a need for novel communication techniques that provide forbandwidth minimization.

It would be beneficial to enhance modern electric vehicles to have acentrally controlled charging program. What is needed are systems andmethods that provide for the complexity of charging intelligence ofsmart vehicles. There is also a need for novel communication techniqueseffectively use existing communication hardware, that allow forupgrading existing equipment, and that do not require specific hardware.In addition, novel systems and methods are needed that effectivelyprovide communication services to vehicle subsystems.

SUMMARY OF THE INVENTION

In an embodiment, a method for managing power flow at a local siteincludes site-level charging of electrical devices by a power flowmanager. The power flow manager runs a smart charging program, andcoordinates charging activities of the electrical devices. Theelectrical devices may be located at the local site. The method includesreceiving site-level information, which is received by the power flowmanager. In addition, power flow decisions are made, by the power flowmanager, based on the site-level information. Further, power flow to theelectrical devices is managed by the power flow manager, wherein thepower flow manager responds to requests.

In another embodiment, a method for managing power flow by optimizingmultiple power flow management strategies includes coordinating chargingactivities of electrical devices. The charge activities are coordinatedby a power flow manager. Power flow services are also controlled by thepower flow manager. A power flow management strategy is chosen by ameta-optimizer, which also chooses the electrical devices to utilize forimplementing the power flow management strategy. The power flowmanagement strategies are implemented by the power flow manager.

In one embodiment, a method for managing power flow using safe failuremodes includes coordinating charging activities of electrical devices bya power flow manager. The method includes detecting a system failureevent by a power flow manager, and implementing a safe failure mode. Thesafe failure mode implemented by the power flow manager provides thatthe charging activities be coordinated in a predictable andnon-disruptive manner.

In another embodiment, a method for managing power flow uses generationstacks of power production to reduce cost of providing power toelectrical devices. This method also includes coordinating chargingactivities of electrical devices by a power flow manager. In addition,the power flow manager controls a power production stack, which ordersavailable power. A dispatchable load is listed in the power productionstack. The dispatchable load is removed based on a cost reductionstrategy.

In an embodiment, a method for managing power flow includes controllingpower resources via Automatic Generation Control (AGC) commands. The AGCcommands are transmitted by a power flow manager to the power resources.The AGC commands request power regulation. The method includesapportioning the power regulation to the power resources based on anapportionment scheme. In addition, the method may include transmittingan AGC command to a power resource, wherein the AGC command requests anapportioned amount of the power regulation from the power resource.

The apportionment scheme may relate to various factors, including: powerrange of each power resource; power range of some power resources;minimization of communications to the power resources; fairness to thepower resources; maximization future abilities to provide power servicesby the power resources; and/or, preferences or requirements of the powerresources.

In another embodiment, the method for managing power flow also includescontrolling a plurality of power resources via Automatic GenerationControl (AGC) commands. The AGC commands are transmitted by a power flowmanager to power resources, and the AGC commands request powerregulation. Further, the method determines a power regulation range fora power resource, and transmits an AGC command to the power resource.The AGC command is based on the power regulation range for the powerresource.

In yet another embodiment, a method for managing power flow may includedetecting a change in an intermittent power flow. Accordingly, a powerflow manager detects the change in the intermittent power flow. Thepower flow manager also coordinates power resources to respond to thechange in the intermittent power flow by implementing a power flowstrategy. The power flow strategy may be a smoothing strategy or aleveling strategy.

In an embodiment, a method for determining the location of devices onpower flow management system using network fingerprints includesreceiving network information. Such network information is associatedwith electric devices, such as electric vehicles. The method includesgenerating a network fingerprint based on the network information, andstoring the network fingerprint in a database. Further, the methodincludes detecting a change in device information for an electricdevices. The changed device information of the electric devices iscompared with the network fingerprint. The location of the electricdevice is determined based on the network fingerprint.

In one embodiment the invention is a method. A plurality of power flowmeasurements are received from each of a plurality of devices. Eachdevice is associated with a power flow and is capable of measuring therespective device's power flow within a measurement error. The pluralityof power flow measurements are aggregated, using a computing device,producing an aggregated power flow measurement. The error bounds of theaggregated power flow measurement are then determined, using thecomputing device, using at least one error model.

In another embodiment the invention is a system. The system comprises: aplurality of devices, each device being associated with a power flow,each of the devices being capable of measuring the respective device'spower flow within a measurement error; an aggregate power measurementmodule comprising one or more processors programmed to execute softwarecode retrieved from a computer readable storage medium storing softwarefor a method. The method comprises the steps of receiving, over anetwork, a plurality of power flow measurements from each of theplurality of devices; aggregating the power flow measurements, producingan aggregated power flow measurement; and determining the error boundsof the aggregated power flow measurement using at least one error model.

In another embodiment, the invention is a method. A device having atleast one DC power flow sensor is augmented with at least one AC powerflow sensor and AC and DC power flows through the device are measuredusing the sensors over a range of operating points. An inference modelof AC power flow in the device as a function of DC power flow is thenbuilt, wherein the error of the model is bounded. The AC power flowsensor can then be removed from the device. The DC power flow throughthe device is then measured and the AC power flow for the device isinferred, using the computing device, using the inference model.

In another embodiment the invention is a system. The system comprises aplurality of endpoint devices, each endpoint device having at least onesensor for measuring power flow through the respective device, whereinone or more of the at least one of sensors are DC sensors. The systemfurther comprises an inference module comprising one or more processorsprogrammed to execute software code retrieved from a computer readablestorage medium storing software for a method comprising the steps:receiving measurements, over a network, from each of the sensors; andinferring an AC power flow of the plurality of endpoint devices usingthe measurements, wherein AC power flow for devices having DC sensors isinferred using an inference model developed by measuring therelationship of AC power flow to DC sensor measurements in devicessimilar to the respective device.

In one embodiment, a system for minimizing network traffic consumptionin a power flow management system includes devices operable to generate,consume, or store electric energy, and a power flow management system,which manages power flow transferred between the plurality of devicesand a power grid. This minimization system also includes a network tocommunicate device information and power flow information between thepower flow management system and the devices. The device information isreceived by the power flow management system. The power flow informationis transmitted by the power flow management system, and includes anenergy rate command received by a devices. The power flow managementsystem reduces consumption of the traffic traversing the network via anetwork traffic consumption reduction technique.

In one embodiment of a system for communications protocol translation ina power flow management system, the system includes networks thatconnect electric devices and electric power supplies. One networkutilizes a communications protocol that is different from thecommunications protocol utilized by another network. A communicationsprotocol translation device communicates with the networks, andformulates messages from one communications protocol to the othercommunications protocol. The reformulated messages pass from one networkto another network.

In an embodiment, a system for communicating in a power flow managementsystem utilizing existing hardware includes a smart charging module thatis configured to be implemented on an server subsystem in a vehicle. Theserver subsystem is connected to a shared vehicle-wide communicationsmedium for communication with another subsystem in the vehicle. Themodule is further configured to provide a set of services usingcapabilities provided by the server subsystem and the other subsystem.These services includes sending messages, using the shared vehicle-widecommunications medium to one subsystem in the vehicle to implement asmart charging program.

In another embodiment, a communications module for providingcommunication services to vehicle subsystems includes a centralprocessing unit in a vehicle and a CAN-bus transceiver operativelyconnected to the central processing unit connected to an external bus inthe vehicle. The external bus is operatively connected to a vehiclesubsystem. The module includes a software stack operatively connected tothe central processing unit configured to wrap communications packets ina CAN header for communications packets entering a vehicle from anexternal network. The software stack is further configured to remove CANheaders for communications packets leaving the vehicle. The moduleincludes software, executed by the central processing unit, configuredto translate messages comprising the communications packets from aremote network format to CAN format. The module also includes software,executed by the central processing unit, configured to support a bondingor provisioning process required by an external communications protocol.

In yet another embodiment, an interface enabling the installation of acharge controller for a control extensibility system includes a physicalinterface to a vehicle's CAN-bus comprising an electrical contact plug.The interface also includes an expansion module providing astandardization of software messages sent over the CAN-bus to controlcharging. In addition, the interface includes a physical location forthe charge controller to reside, where the CAN interface plug islocated.

In an embodiment, an interface enabling an electric vehicle tocommunicate with an electric power supply device without specifichardware includes transmitting information from an electrical loadassociated with the electric vehicle to an electric power supply bymodulating the power transfer between the electrical load and anelectric power supply.

In another embodiment, a system for arbitrating a smart chargepointincludes a first smart charging module that is configured to beimplemented on equipment located inside a vehicle. The first smartcharging module is configured to communicate with a server implementinga smart charging program. The smart charging program coordinating thecharging activities of a plurality of vehicles distributed over an area.The first smart charging module is moderates electrical load in thevehicle by reducing the power consumption of the vehicle. In addition,the first smart charging module communicates with a second smartcharging module in external equipment responsible for providingelectricity to the vehicle, enabling the first smart charging module andthe second smart charging module to implement a charge coordinationprotocol to determine which of the two modules is responsible forcommunicating with the server implementing the smart charging program.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of theinvention will be apparent from the following more particulardescription of embodiments as illustrated in the accompanying drawings,in which reference characters refer to the same parts throughout thevarious views. The drawings are not necessarily to scale, emphasisinstead being placed upon illustrating principles of the invention.

FIG. 1 is a diagram of an example of a power aggregation system.

FIGS. 2A-2B are diagrams of an example of connections between anelectric vehicle, the power grid, and the Internet.

FIG. 3 is a block diagram of an example of connections between anelectric resource and a flow control server of the power aggregationsystem.

FIG. 4 is a diagram of an example of a layout of the power aggregationsystem.

FIG. 5 is a diagram of an example of control areas in the poweraggregation system.

FIG. 6 is a diagram of multiple flow control centers in the poweraggregation system and a directory server for determining a flow controlcenter.

FIG. 7 is a block diagram of an example of flow control server.

FIG. 8A is a block diagram of an example of remote intelligent powerflow module.

FIG. 8B is a block diagram of an example of transceiver and chargingcomponent combination.

FIG. 8C is an illustration of an example of simple user interface forfacilitating user controlled charging.

FIG. 9 is a diagram of an example of resource communication protocol.

FIG. 10 is a diagram of an example of a site power flow manager.

FIG. 11 is a flow chart of an example of a site power flow manager.

FIG. 12 is a flow chart of an example of optimization across multiplepower flow management strategies.

FIG. 13 is a flow chart of an example of avoiding power spikes duringenergy management failures using safe failure modes.

FIG. 14 is a flow chart of an example of generation-stack-aware dispatchof resources.

FIG. 15 is a flow chart of an example for AGC virtualization.

FIG. 16 is a flow chart of an example for AGC for resources beyondgeneration.

FIG. 17 is a flow chart of an example of smoothing and levelingintermittent generation.

FIG. 18 is a flow chart of an example of fingerprinting a local networkfor a power management system, in accordance with the currentlydisclosed invention.

FIG. 19 is a flow chart of an example of determining the location of anelectric vehicle using a network fingerprint.

FIG. 20 is a block diagram illustrating a method for inferring anaggregate power flow for a power management system.

FIG. 21 is a block diagram illustrating a method for inferring AC powerflow in a device from DC measurements.

FIG. 22 is a flow chart of an example of a bandwidth minimizationtechnique.

FIG. 23 is a flow chart of an example of a protocol translation system.

FIG. 24 is a block diagram of an example of a communications protocoltranslation device.

FIG. 25 is a diagram of an example of communications using existinghardware.

FIG. 26 is a diagram of an example of communication services to vehiclesubsystems.

FIG. 27 is a diagram of an example of an extensibility system.

FIG. 28 is a diagram of an example of communications without specifichardware.

FIG. 29 is a diagram of an example of arbitrating a smart charge point.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings.

Overview

Described herein is a power aggregation system for distributed electricresources, and associated methods. In one implementation, a systemcommunicates over the Internet and/or some other public or privatenetworks with numerous individual electric resources connected to apower grid (hereinafter, “grid”). By communicating, the system candynamically aggregate these electric resources to provide power servicesto grid operators (e.g. utilities, Independent System Operators (ISO),etc.).

“Power services” as used herein, refers to energy delivery as well asother ancillary services including demand response, regulation, spinningreserves, non-spinning reserves, energy imbalance, reactive power, andsimilar products.

“Aggregation” as used herein refers to the ability to control powerflows into and out of a set of spatially distributed electric resourceswith the purpose of providing a power service of larger magnitude.

“Charge Control Management” as used herein refers to enabling orperforming the starting, stopping, or level-setting of a flow of powerbetween a power grid and an electric resource.

“Power grid operator” as used herein, refers to the entity that isresponsible for maintaining the operation and stability of the powergrid within or across an electric control area. The power grid operatormay constitute some combination of manual/human action/intervention andautomated processes controlling generation signals in response to systemsensors. A “control area operator” is one example of a power gridoperator.

“Control area” as used herein, refers to a contained portion of theelectrical grid with defined input and output ports. The net flow ofpower into this area must equal (within some error tolerance) the sum ofthe power consumption within the area and power outflow from the area.

“Power grid” as used herein means a power distribution system/networkthat connects producers of power with consumers of power. The networkmay include generators, transformers, interconnects, switching stations,and safety equipment as part of either/both the transmission system(i.e., bulk power) or the distribution system (i.e. retail power). Thepower aggregation system is vertically scalable for use within aneighborhood, a city, a sector, a control area, or (for example) one ofthe eight large-scale Interconnects in the North American ElectricReliability Council (NERC). Moreover, the system is horizontallyscalable for use in providing power services to multiple grid areassimultaneously.

“Grid conditions” as used herein, refers to the need for more or lesspower flowing in or out of a section of the electric power grid, inresponse to one of a number of conditions, for example supply changes,demand changes, contingencies and failures, ramping events, etc. Thesegrid conditions typically manifest themselves as power quality eventssuch as under- or over-voltage events or under- or over-frequencyevents.

“Power quality events” as used herein typically refers to manifestationsof power grid instability including voltage deviations and frequencydeviations; additionally, power quality events as used herein alsoincludes other disturbances in the quality of the power delivered by thepower grid such as sub-cycle voltage spikes and harmonics.

“Electric resource” as used herein typically refers to electricalentities that can be commanded to do some or all of these three things:take power (act as load), provide power (act as power generation orsource), and store energy. Examples may include battery/charger/invertersystems for electric or hybrid-electric vehicles, repositories ofused-but-serviceable electric vehicle batteries, fixed energy storage,fuel cell generators, emergency generators, controllable loads, etc.

“Electric vehicle” is used broadly herein to refer to pure electric andhybrid electric vehicles, such as plug-in hybrid electric vehicles(PHEVs), especially vehicles that have significant storage batterycapacity and that connect to the power grid for recharging the battery.More specifically, electric vehicle means a vehicle that gets some orall of its energy for motion and other purposes from the power grid.Moreover, an electric vehicle has an energy storage system, which mayconsist of batteries, capacitors, etc., or some combination thereof. Anelectric vehicle may or may not have the capability to provide powerback to the electric grid.

Electric vehicle “energy storage systems” (batteries, super capacitors,and/or other energy storage devices) are used herein as a representativeexample of electric resources intermittently or permanently connected tothe grid that can have dynamic input and output of power. Such batteriescan function as a power source or a power load. A collection ofaggregated electric vehicle batteries can become a statistically stableresource across numerous batteries, despite recognizable tidalconnection trends (e.g., an increase in the total number of vehiclesconnected to the grid at night; a downswing in the collective number ofconnected batteries as the morning commute begins, etc.) Across vastnumbers of electric vehicle batteries, connection trends are predictableand such batteries become a stable and reliable resource to call upon,should the grid or a part of the grid (such as a person's home in ablackout) experience a need for increased or decreased power. Datacollection and storage also enable the power aggregation system topredict connection behavior on a per-user basis.

An Example of the Presently Disclosed System

FIG. 1 shows a power aggregation system 100. A flow control center 102is communicatively coupled with a network, such as a public/private mixthat includes the Internet 104, and includes one or more servers 106providing a centralized power aggregation service. “Internet” 104 willbe used herein as representative of many different types ofcommunicative networks and network mixtures (e.g., one or more wide areanetworks—public or private—and/or one or more local area networks). Viaa network, such as the Internet 104, the flow control center 102maintains communication 108 with operators of power grid(s), andcommunication 110 with remote resources, i.e., communication withperipheral electric resources 112 (“end” or “terminal” nodes/devices ofa power network) that are connected to the power grid 114. In oneimplementation, power line communicators (PLCs), such as those thatinclude or consist of Ethernet-over-power line bridges 120 areimplemented at connection locations so that the “last mile” (in thiscase, last feet—e.g., in a residence 124) of Internet communication withremote resources is implemented over the same wire that connects eachelectric resource 112 to the power grid 114. Thus, each physicallocation of each electric resource 112 may be associated with acorresponding Ethernet-over-power line bridge 120 (hereinafter,“bridge”) at or near the same location as the electric resource 112.Each bridge 120 is typically connected to an Internet access point of alocation owner, as will be described in greater detail below. Thecommunication medium from flow control center 102 to the connectionlocation, such as residence 124, can take many forms, such as cablemodem, DSL, satellite, fiber, WiMax, etc. In a variation, electricresources 112 may connect with the Internet by a different medium thanthe same power wire that connects them to the power grid 114. Forexample, a given electric resource 112 may have its own wirelesscapability to connect directly with the Internet 104 or an Internetaccess point and thereby with the flow control center 102.

Electric resources 112 of the power aggregation system 100 may includethe batteries of electric vehicles connected to the power grid 114 atresidences 124, parking lots 126 etc.; batteries in a repository 128,fuel cell generators, private dams, conventional power plants, and otherresources that produce electricity and/or store electricity physicallyor electrically.

In one implementation, each participating electric resource 112 or groupof local resources has a corresponding remote intelligent power flow(IPF) module 134 (hereinafter, “remote IPF module” 134). The centralizedflow control center 102 administers the power aggregation system 100 bycommunicating with the remote IPF modules 134 distributed peripherallyamong the electric resources 112. The remote IPF modules 134 performseveral different functions, including, but not limited to, providingthe flow control center 102 with the statuses of remote resources;controlling the amount, direction, and timing of power being transferredinto or out of a remote electric resource 112; providing metering ofpower being transferred into or out of a remote electric resource 112;providing safety measures during power transfer and changes ofconditions in the power grid 114; logging activities; and providingself-contained control of power transfer and safety measures whencommunication with the flow control center 102 is interrupted. Theremote IPF modules 134 will be described in greater detail below.

In another implementation, instead of having an IPF module 134, eachelectric resource 112 may have a corresponding transceiver (not shown)to communicate with a local charging component (not shown). Thetransceiver and charging component, in combination, may communicate withflow control center 102 to perform some or all of the above mentionedfunctions of IPF module 134. A transceiver and charging component areshown in FIG. 2B and are described in greater detail herein.

FIG. 2A shows another view of electrical and communicative connectionsto an electric resource 112. In this example, an electric vehicle 200includes a battery bank 202 and a remote IPF module 134. The electricvehicle 200 may connect to a conventional wall receptacle (wall outlet)204 of a residence 124, the wall receptacle 204 representing theperipheral edge of the power grid 114 connected via a residentialpowerline 206.

In one implementation, the power cord 208 between the electric vehicle200 and the wall outlet 204 can be composed of only conventional wireand insulation for conducting alternating current (AC) power to and fromthe electric vehicle 200. In FIG. 2A, a location-specific connectionlocality module 210 performs the function of network access point—inthis case, the Internet access point. A bridge 120 intervenes betweenthe receptacle 204 and the network access point so that the power cord208 can also carry network communications between the electric vehicle200 and the receptacle 204. With such a bridge 120 and connectionlocality module 210 in place in a connection location, no other specialwiring or physical medium is needed to communicate with the remote IPFmodule 134 of the electric vehicle 200 other than a conventional powercord 208 for providing residential line current at any conventionalvoltage. Upstream of the connection locality module 210, power andcommunication with the electric vehicle 200 are resolved into thepowerline 206 and an Internet cable 104.

Alternatively, the power cord 208 may include safety features not foundin conventional power and extension cords. For example, an electricalplug 212 of the power cord 208 may include electrical and/or mechanicalsafeguard components to prevent the remote IPF module 134 fromelectrifying or exposing the male conductors of the power cord 208 whenthe conductors are exposed to a human user.

In some embodiments, a radio frequency (RF) bridge (not shown) mayassist the remote IPF module 134 in communicating with a foreign system,such as a utility smart meter (not shown) and/or a connection localitymodule 210. For example, the remote IPF module 134 may be equipped tocommunicate over power cord 208 or to engage in some form of RFcommunication, such as Zigbee or Bluetooth™, and the foreign system maybe able to engage in a different form of RF communication. In such animplementation, the RF bridge may be equipped to communicate with boththe foreign system and remote IPF module 134 and to translatecommunications from one to a form the other may understand, and to relaythose messages. In various embodiments, the RF bridge may be integratedinto the remote IPF module 134 or foreign system, or may be external toboth. The communicative associations between the RF bridge and remoteIPF module 134 and between the RF bridge and foreign system may be viawired or wireless communication.

FIG. 2B shows a further view of electrical and communicative connectionsto an electric resource 112. In this example, the electric vehicle 200may include a transceiver 212 rather than a remote IPF module 134. Thetransceiver 212 may be communicatively coupled to a charging component214 through a connection 216, and the charging component itself may becoupled to a conventional wall receptacle (wall outlet) 204 of aresidence 124 and to electric vehicle 200 through a power cord 208. Theother components shown in FIG. 2B may have the couplings and functionsdiscussed with regard to FIG. 2A.

In various embodiments, transceiver 212 and charging component 214 may,in combination, perform the same functions as the remote IPF module 134.Transceiver 212 may interface with computer systems of electric vehicle200 and communicate with charging component 214, providing chargingcomponent 214 with information about electric vehicle 200, such as itsvehicle identifier, a location identifier, and a state of charge. Inresponse, transceiver 212 may receive requests and commands whichtransceiver 212 may relay to vehicle 200's computer systems.

Charging component 214, being coupled to both electric vehicle 200 andwall outlet 204, may effectuate charge control of the electric vehicle200. If the electric vehicle 200 is not capable of charge controlmanagement, charging component 214 may directly manage the charging ofelectric vehicle 200 by stopping and starting a flow of power betweenthe electric vehicle 200 and a power grid 114 in response to commandsreceived from a flow control server 106. If, on the other hand, theelectric vehicle 200 is capable of charge control management, chargingcomponent 214 may effectuate charge control by sending commands to theelectric vehicle 200 through the transceiver 212.

In some embodiments, the transceiver 212 may be physically coupled tothe electric vehicle 200 through a data port, such as an OBD-IIconnector. In other embodiments, other couplings may be used. Theconnection 216 between transceiver 212 and charging component 214 may bea wireless signal, such as a radio frequency (RF), such as a Zigbee, orBluetooth™ signal. And charging component 214 may include a receiversocket to couple with power cord 208 and a plug to couple with walloutlet 204. In one embodiment, charging component 214 may be coupled toconnection locality module 210 in either a wired or wireless fashion.For example, charging component 214 might have a data interface forcommunicating wirelessly with both the transceiver 212 and localitymodule 210. In such an embodiment, the bridge 120 may not be required.

Further details about the transceiver 212 and charging component 214 areillustrated by FIG. 8B and described in greater detail herein.

FIG. 3 shows another implementation of the connection locality module210 of FIG. 2, in greater detail. In FIG. 3, an electric resource 112has an associated remote IPF module 134, including a bridge 120. Thepower cord 208 connects the electric resource 112 to the power grid 114and also to the connection locality module 210 in order to communicatewith the flow control server 106.

The connection locality module 210 includes another instance of a bridge120, connected to a network access point 302, which may include suchcomponents as a router, switch, and/or modem, to establish a hardwiredor wireless connection with, in this case, the Internet 104. In oneimplementation, the power cord 208 between the two bridges 120 and 120′is replaced by a wireless Internet link, such as a wireless transceiverin the remote IPF module 134 and a wireless router in the connectionlocality module 210.

In other embodiments, a transceiver 212 and charging component 214 maybe used instead of a remote IPF module 134. In such an embodiment, thecharging component 214 may include or be coupled to a bridge 120, andthe connection locality module 210 may also include a bridge 120′, asshown. In yet other embodiments, not shown, charging component 214 andconnection locality module 210 may communicate in a wired or wirelessfashion, as mentioned previously, without bridges 120 and 120′. Thewired or wireless communication may utilize any sort of connectiontechnology known in the art, such as Ethernet or RF communication, suchas Zigbee, or Bluetooth™.

System Layouts

FIG. 4 shows a layout 400 of the power aggregation system 100. The flowcontrol center 102 can be connected to many different entities, e.g.,via the Internet 104, for communicating and receiving information. Thelayout 400 includes electric resources 112, such as plug-in electricvehicles 200, physically connected to the grid within a single controlarea 402. The electric resources 112 become an energy resource for gridoperators 404 to utilize.

The layout 400 also includes end users 406 classified into electricresource owners 408 and electrical connection location owners 410, whomay or may not be one and the same. In fact, the stakeholders in a poweraggregation system 100 include the system operator at the flow controlcenter 102, the grid operator 404, the resource owner 408, and the ownerof the location 410 at which the electric resource 112 is connected tothe power grid 114.

Electrical connection location owners 410 can include:

Rental Car Lots—rental car companies often have a large portion of theirfleet parked in the lot. They can purchase fleets of electric vehicles200 and, participating in a power aggregation system 100, generaterevenue from idle fleet vehicles.

Public Parking Lots—parking lot owners can participate in the poweraggregation system 100 to generate revenue from parked electric vehicles200. Vehicle owners can be offered free parking, or additionalincentives, in exchange for providing power services.

Workplace Parking—employers can participate in a power aggregationsystem 100 to generate revenue from parked employee electric vehicles200. Employees can be offered incentives in exchange for providing powerservices.

Residences—a home garage can merely be equipped with a connectionlocality module 210 to enable the homeowner to participate in the poweraggregation system 100 and generate revenue from a parked car. Also, thevehicle battery 202 and associated power electronics within the vehiclecan provide local power backup power during times of peak load or poweroutages.

Residential Neighborhoods—neighborhoods can participate in a poweraggregation system 100 and be equipped with power-delivery devices(deployed, for example, by homeowner cooperative groups) that generaterevenue from parked electric vehicles 200.

The grid operations 116 of FIG. 4 collectively include interactions withenergy markets 412, the interactions of grid operators 404, and theinteractions of automated grid controllers 118 that perform automaticphysical control of the power grid 114.

The flow control center 102 may also be coupled with information sources414 for input of weather reports, events, price feeds, etc. Other datasources 414 include the system stakeholders, public databases, andhistorical system data, which may be used to optimize system performanceand to satisfy constraints on the power aggregation system 100.

Thus, a power aggregation system 100 may consist of components that:

-   communicate with the electric resources 112 to gather data and    actuate charging/discharging of the electric resources 112;-   gather real-time energy prices;-   gather real-time resource statistics;-   predict behavior of electric resources 112 (connectedness, location,    state (such as battery State-Of-Charge) at a given time of interest,    such as a time of connect/disconnect);-   predict behavior of the power grid 114/load;-   encrypt communications for privacy and data security;-   actuate charging of electric vehicles 200 to optimize some figure(s)    of merit;-   offer guidelines or guarantees about load availability for various    points in the future, etc.

These components can be running on a single computing resource(computer, etc.), or on a distributed set of resources (eitherphysically co-located or not).

Power aggregation systems 100 in such a layout 400 can provide manybenefits: for example, lower-cost ancillary services (i.e., powerservices), fine-grained (both temporal and spatial) control overresource scheduling, guaranteed reliability and service levels,increased service levels via intelligent resource scheduling, and/orfirming of intermittent generation sources such as wind and solar powergeneration.

The power aggregation system 100 enables a grid operator 404 to controlthe aggregated electric resources 112 connected to the power grid 114.An electric resource 112 can act as a power source, load, or storage,and the resource 112 may exhibit combinations of these properties.Control of a set of electric resources 112 is the ability to actuatepower consumption, generation, or energy storage from an aggregate ofthese electric resources 112.

FIG. 5 shows the role of multiple control areas 402 in the poweraggregation system 100. Each electric resource 112 can be connected tothe power aggregation system 100 within a specific electrical controlarea. A single instance of the flow control center 102 can administerelectric resources 112 from multiple distinct control areas 501 (e.g.,control areas 502, 504, and 506). In one implementation, thisfunctionality is achieved by logically partitioning resources within thepower aggregation system 100. For example, when the control areas 402include an arbitrary number of control areas, control area “A” 502,control area “B” 504, . . . , control area “n” 506, then grid operations116 can include corresponding control area operators 508, 510, . . . ,and 512. Further division into a control hierarchy that includes controldivision groupings above and below the illustrated control areas 402allows the power aggregation system 100 to scale to power grids 114 ofdifferent magnitudes and/or to varying numbers of electric resources 112connected with a power grid 114.

FIG. 6 shows a layout 600 of a power aggregation system 100 that usesmultiple centralized flow control centers 102 and 102′ and a directoryserver 602 for determining a flow control center. Each flow controlcenter 102 and 102′ has its own respective end users 406 and 406′.Control areas 402 to be administered by each specific instance of a flowcontrol center 102 can be assigned dynamically. For example, a firstflow control center 102 may administer control area A 502 and controlarea B 504, while a second flow control center 102′ administers controlarea n 506. Likewise, corresponding control area operators (508, 510,and 512) are served by the same flow control center 102 that servestheir respective different control areas.

In various embodiments, an electric resource may determine which flowcontrol center 102/102′ administers its control area 502/504/506 bycommunicating with a directory server 602. The address of the directoryserver 602 may be known to electric resource 112 or its associated IPFmodule 134 or charging component 214. Upon plugging in, the electricresource 112 may communicate with the directory server 602, providingthe directory server 112 with a resource identifier and/or a locationidentifier. Based on this information, the directory server 602 mayrespond, identifying which flow control center 102/102′ to use.

In another embodiment, directory server 602 may be integrated with aflow control server 106 of a flow control center 102/102′. In such anembodiment, the electric resource 112 may contact the server 106. Inresponse, the server 106 may either interact with the electric resource112 itself or forward the connection to another flow control center102/102′ responsible for the location identifier provided by theelectric resource 112.

In some embodiments, whether integrated with a flow control server 106or not, directory server 602 may include a publicly accessible databasefor mapping locations to flow control centers 102/102′.

Flow Control Server

FIG. 7 shows a server 106 of the flow control center 102. Theillustrated implementation in FIG. 7 is only one example configuration,for descriptive purposes. Many other arrangements of the illustratedcomponents or even different components constituting a server 106 of theflow control center 102 are possible within the scope of the subjectmatter. Such a server 106 and flow control center 102 can be executed inhardware, software, or combinations of hardware, software, firmware,etc.

The flow control server 106 includes a connection manager 702 tocommunicate with electric resources 112, a prediction engine 704 thatmay include a learning engine 706 and a statistics engine 708, aconstraint optimizer 710, and a grid interaction manager 712 to receivegrid control signals 714. Grid control signals 714 are sometimesreferred to as generation control signals, such as automated generationcontrol (AGC) signals. The flow control server 106 may further include adatabase/information warehouse 716, a web server 718 to present a userinterface to electric resource owners 408, grid operators 404, andelectrical connection location owners 410; a contract manager 720 tonegotiate contract terms with energy markets 412, and an informationacquisition engine 414 to track weather, relevant news events, etc., anddownload information from public and private databases 722 forpredicting behavior of large groups of the electric resources 112,monitoring energy prices, negotiating contracts, etc.

Remote IPF Module

FIG. 8A shows the remote IPF module 134 of FIGS. 1 and 2 in greaterdetail. The illustrated remote IPF module 134 is only one exampleconfiguration, for descriptive purposes. Many other arrangements of theillustrated components or even different components constituting aremote IPF module 134 are possible within the scope of the subjectmatter. Such a remote IPF module 134 has some hardware components andsome components that can be executed in hardware, software, orcombinations of hardware, software, firmware, etc. In other embodiments,executable instructions configured to perform some or all of theoperations of remote IPF module 134 may be added to hardware of anelectric resource 112 such as an electric vehicle that, when combinedwith the executable instructions, provides equivalent functionality toremote IPF module 134. References to remote IPF module 134 as usedherein include such executable instructions.

The illustrated example of a remote IPF module 134 is represented by animplementation suited for an electric vehicle 200. Thus, some vehiclesystems 800 are included as part of the remote IPF module 134 for thesake of description. However, in other implementations, the remote IPFmodule 134 may exclude some or all of the vehicles systems 800 frombeing counted as components of the remote IPF module 134.

The depicted vehicle systems 800 include a vehicle computer and datainterface 802, an energy storage system, such as a battery bank 202, andan inverter/charger 804. Besides vehicle systems 800, the remote IPFmodule 134 also includes a communicative power flow controller 806. Thecommunicative power flow controller 806 in turn includes some componentsthat interface with AC power from the grid 114, such as a powerlinecommunicator, for example an Ethernet-over-powerline bridge 120, and acurrent or current/voltage (power) sensor 808, such as a current sensingtransformer.

The communicative power flow controller 806 also includes Ethernet andinformation processing components, such as a processor 810 ormicrocontroller and an associated Ethernet media access control (MAC)address 812; volatile random access memory 814, nonvolatile memory 816or data storage, an interface such as an RS-232 interface 818 or aCANbus interface 820; an Ethernet physical layer interface 822, whichenables wiring and signaling according to Ethernet standards for thephysical layer through means of network access at the MAC/Data LinkLayer and a common addressing format. The Ethernet physical layerinterface 822 provides electrical, mechanical, and procedural interfaceto the transmission medium—i.e., in one implementation, using theEthernet-over-powerline bridge 120. In a variation, wireless or othercommunication channels with the Internet 104 are used in place of theEthernet-over-powerline bridge 120.

The communicative power flow controller 806 also includes abidirectional power flow meter 824 that tracks power transfer to andfrom each electric resource 112, in this case the battery bank 202 of anelectric vehicle 200.

The communicative power flow controller 806 operates either within, orconnected to an electric vehicle 200 or other electric resource 112 toenable the aggregation of electric resources 112 introduced above (e.g.,via a wired or wireless communication interface). These above-listedcomponents may vary among different implementations of the communicativepower flow controller 806, but implementations typically include:

-   an intra-vehicle communications mechanism that enables communication    with other vehicle components;-   a mechanism to communicate with the flow control center 102;-   a processing element;-   a data storage element;-   a power meter; and-   optionally, a user interface.

Implementations of the communicative power flow controller 806 canenable functionality including:

-   executing pre-programmed or learned behaviors when the electric    resource 112 is offline (not connected to Internet 104, or service    is unavailable);-   storing locally-cached behavior profiles for “roaming” connectivity    (what to do when charging on a foreign system, i.e., when charging    in the same utility territory on a foreign meter or in a separate    utility territory, or in disconnected operation, i.e., when there is    no network connectivity);-   allowing the user to override current system behavior; and-   metering power-flow information and caching meter data during    offline operation for later transaction.

Thus, the communicative power flow controller 806 includes a centralprocessor 810, interfaces 818 and 820 for communication within theelectric vehicle 200, a powerline communicator, such as anEthernet-over-powerline bridge 120 for communication external to theelectric vehicle 200, and a power flow meter 824 for measuring energyflow to and from the electric vehicle 200 via a connected AC powerline208.

Power Flow Meter

Power is the rate of energy consumption per interval of time. Powerindicates the quantity of energy transferred during a certain period oftime, thus the units of power are quantities of energy per unit of time.The power flow meter 824 measures power for a given electric resource112 across a bidirectional flow—e.g., power from grid 114 to electricvehicle 200 or from electric vehicle 200 to the grid 114. In oneimplementation, the remote IPF module 134 can locally cache readingsfrom the power flow meter 824 to ensure accurate transactions with thecentral flow control server 106, even if the connection to the server isdown temporarily, or if the server itself is unavailable.

Transceiver and Charging Component

FIG. 8B shows the transceiver 212 and charging component 214 of FIG. 2Bin greater detail. The illustrated transceiver 212 and chargingcomponent 214 is only one example configuration, for descriptivepurposes. Many other arrangements of the illustrated components or evendifferent components constituting the transceiver 212 and chargingcomponent 214 are possible within the scope of the subject matter. Sucha transceiver 212 and charging component 214 have some hardwarecomponents and some components that can be executed in hardware,software, or combinations of hardware, software, firmware, etc.

The illustrated example of the transceiver 212 and charging component214 is represented by an implementation suited for an electric vehicle200. Thus, some vehicle systems 800 are illustrated to provide contextto the transceiver 212 and charging component 214 components.

The depicted vehicle systems 800 include a vehicle computer and datainterface 802, an energy storage system, such as a battery bank 202, andan inverter/charger 804. In some embodiments, vehicle systems 800 mayinclude a data port, such as an OBD-II port, that is capable ofphysically coupling with the transceiver 212. The transceiver 212 maythen communicate with the vehicle computer and data interface 802through the data port, receiving information from electric resource 112comprised by vehicle systems 800 and, in some embodiments, providingcommands to the vehicle computer and data interface 802. In oneimplementation, the vehicle computer and data interface 802 may becapable of charge control management. In such an embodiment, the vehiclecomputer and data interface 802 may perform some or all of the chargingcomponent 214 operations discussed below. In other embodiments,executable instructions configured to perform some or all of theoperations of the vehicle computer and data interface 802 may be addedto hardware of an electric resource 112 such as an electric vehiclethat, when combined with the executable instructions, providesequivalent functionality to the vehicle computer and data interface 802.References to the vehicle computer and data interface 802 as used hereininclude such executable instructions.

In various embodiments, the transceiver 212 may have a physical formthat is capable of coupling to a data port of vehicle systems 800. Sucha transceiver 212 may also include a plurality of interfaces, such as anRS-232 interface 818 and/or a CANBus interface 820. In variousembodiments, the RS-232 interface 818 or CANBus interface 820 may enablethe transceiver 212 to communicate with the vehicle computer and datainterface 802 through the data port. Also, the transceiver may be orcomprise an additional interface (not shown) capable of engaging inwireless communication with a data interface 820 of the chargingcomponent 214. The wireless communication may be of any form known inthe art, such as radio frequency (RF) communication (e.g., Zigbee,and/or Bluetooth™ communication). In other embodiments, the transceivermay comprise a separate conductor or may be configured to utilize apowerline 208 to communicate with charging component 214. In yet otherembodiments, not shown, transceiver 212 may simply be a radio frequencyidentification (RFID) tag capable of storing minimal information aboutthe electric resource 112, such as a resource identifier, and of beingread by a corresponding RFID reader of charging component 214. In suchother embodiments, the RFID tag might not couple with a data port orcommunicate with the vehicle computer and data interface 802.

As shown, the charging component 214 may be an intelligent plug devicethat is physically connected to a charging medium, such as a powerline208 (the charging medium coupling the charging component 214 to theelectric resource 112) and an outlet of a power grid (such as the walloutlet 204 shown in FIG. 2B). In other embodiments charging component214 may be a charging station or some other external control. In someembodiments, the charging component 214 may be portable.

In various embodiments, the charging component 214 may includecomponents that interface with AC power from the grid 114, such as apowerline communicator, for example an Ethernet-over-powerline bridge120, and a current or current/voltage (power) sensor 808, such as acurrent sensing transformer.

In other embodiments, the charging component 214 may include a furtherEthernet plug or wireless interface in place of bridge 120. In such anembodiment, data-over-powerline communication is not necessary,eliminating the need for a bridge 120. The Ethernet plug or wirelessinterface may communicate with a local access point, and through thataccess point to flow control server 106.

The charging component 214 may also include Ethernet and informationprocessing components, such as a processor 810 or microcontroller and anassociated Ethernet media access control (MAC) address 812; volatilerandom access memory 814, nonvolatile memory 816 or data storage, a datainterface 826 for communicating with the transceiver 212, and anEthernet physical layer interface 822, which enables wiring andsignaling according to Ethernet standards for the physical layer throughmeans of network access at the MAC/Data Link Layer and a commonaddressing format. The Ethernet physical layer interface 822 provideselectrical, mechanical, and procedural interface to the transmissionmedium—i.e., in one implementation, using the Ethernet-over-powerlinebridge 120. In a variation, wireless or other communication channelswith the Internet 104 are used in place of the Ethernet-over-powerlinebridge 120.

The charging component 214 may also include a bidirectional power flowmeter 824 that tracks power transfer to and from each electric resource112, in this case the battery bank 202 of an electric vehicle 200.

Further, in some embodiments, the charging component 214 may comprise anRFID reader to read the electric resource information from transceiver212 when transceiver 212 is an RFID tag.

Also, in various embodiments, the charging component 214 may include acredit card reader to enable a user to identify the electric resource112 by providing credit card information. In such an embodiment, atransceiver 212 may not be necessary.

Additionally, in one embodiment, the charging component 214 may includea user interface, such as one of the user interfaces described ingreater detail below.

Implementations of the charging component 214 can enable functionalityincluding:

-   executing pre-programmed or learned behaviors when the electric    resource 112 is offline (not connected to Internet 104, or service    is unavailable);-   storing locally-cached behavior profiles for “roaming” connectivity    (what to do when charging on a foreign system or in disconnected    operation, i.e., when there is no network connectivity);-   allowing the user to override current system behavior; and-   metering power-flow information and caching meter data during    offline operation for later transaction.

User Interfaces (UI)

Charging Station UI. An electrical charging station, whether free or forpay, can be installed with a user interface that presents usefulinformation to the user. Specifically, by collecting information aboutthe grid 114, the electric resource state, and the preferences of theuser, the station can present information such as the currentelectricity price, the estimated recharge cost, the estimated time untilrecharge, the estimated payment for uploading power to the grid 114(either total or per hour), etc. The information acquisition engine 414communicates with the electric resource 112 and with public and/orprivate data networks 722 to acquire the data used in calculating thisinformation.

The types of information gathered from the electric resource 112 couldinclude an electric resource identifier (resource ID) and stateinformation like the state of charge of the electric resource 112. Theresource ID could be used to obtain knowledge of the electric resourcetype and capabilities, preferences, etc. through lookup with the flowcontrol server 106.

In various embodiments, the charging station system including the UImight also gather grid-based information, such as current and futureenergy costs at the charging station.

User Charge Control UI Mechanisms. In various embodiments, by default,electric resources 112 may receive charge control management via poweraggregation system 100. In some embodiments, an override control may beprovided to override charge control management and charge as soon aspossible. The override control may be provided, in various embodiments,as a user interface mechanism of the remote IPF module 134, the chargingcomponent 214, of the electric resource (for example, if electricresource is a vehicle 200, the user interface control may be integratedwith dash controls of the vehicle 200) or even via a web page offered byflow control server 106. The control could be presented, for example, asa button, a touch screen option, a web page, or some other UI mechanism.In one embodiment, the UI may be the UI illustrated by FIG. 8C anddiscussed in greater detail below. In some embodiments, the overridewould be a one-time override, only applying to a single plug-in session.Upon disconnecting and reconnecting, the user may again need to interactwith the UI mechanism to override the charge control management.

In some embodiments, the user may pay more to charge with the overrideon than under charge control management, thus providing an incentive forthe user to accept charge control management. Such a cost differentialmay be displayed or rendered to the user in conjunction with or on theUI mechanism. This differential could take into account time-varyingpricing, such as Time of Use (TOU), Critical Peak Pricing (CPP), andReal-Time Pricing (RTP) schemes, as discussed above, as well as anyother incentives, discounts, or payments that might be forgone by notaccepting charge control management.

UI Mechanism for Management Preferences. In various embodiments, a userinterface mechanism of the remote IPF module 134, the charging component214, of the electric resource (for example, if electric resource is avehicle 200, the user interface control may be integrated with dashcontrols of the vehicle 200) or even via a web page offered by flowcontrol server 106 may enable a user to enter and/or edit managementpreferences to affect charge control management of the user's electricresource 112. In some embodiments, the UI mechanism may allow the userto enter/edit general preferences, such as whether charge controlmanagement is enabled, whether vehicle-to-grid power flow is enabled orwhether the electric resource 112 should only be charged withclean/green power. Also, in various embodiments, the UI mechanism mayenable a user to prioritize relative desires for minimizing costs,maximizing payments (i.e., fewer charge periods for higher amounts),achieving a full state-of-charge for the electric resource 112, chargingas rapidly as possible, and/or charging in as environmentally-friendly away as possible. Additionally, the UI mechanism may enable a user toprovide, a default schedule for when the electric resource will be used(for example, if resource 112 is a vehicle 200, the schedule would befor when the vehicle 200 should be ready to drive). Further, the UImechanism may enable the user to add or select special rules, such as arule not to charge if a price threshold is exceeded or a rule to onlyuse charge control management if it will earn the user at least aspecified threshold of output. Charge control management may then beeffectuated based on any part or all of these user entered preferences.

Simple User Interface. FIG. 8C illustrates a simple user interface (UI)which enables a user to control charging based on selecting among alimited number of high level preferences. For example, UI 2300 includesthe categories “green”, “fast”, and “cheap” (with what is considered“green”, “fast”, and “cheap” varying from embodiment to embodiment). Thecategories shown in UI 2300 are selected only for the sake ofillustration and may instead includes these and/or any other categoriesapplicable to electric resource 112 charging known in the art. As shown,the UI 2300 may be very basic, using well known form controls such asradio buttons. In other embodiments, other graphic controls known in theart may be used. The general categories may be mapped to specificcharging behaviors, such as those discussed above, by a flow controlserver 106.

Electric Resource Communication Protocol

FIG. 9 illustrates a resource communication protocol. As shown, a remoteIPF module 134 or charging component 214 may be in communication with aflow control server 106 over the Internet 104 or another networkingfabric or combination of networking fabrics. In various embodiments, aprotocol specifying an order of messages and/or a format for messagesmay be used to govern the communications between the remote IPF module134 or charging component 214 and flow control server 106.

In some embodiments, the protocol may include two channels, one formessages initiated by the remote IPF module 134 or charging component214 and for replies to those messages from the flow control server 106,and another channel for messages initiated by the flow control server106 and for replies to those messages from the remote IPF module 134 orcharging component 214. The channels may be asynchronous with respect toeach other (that is, initiation of messages on one channel may beentirely independent of initiation of messages on the other channel).However, each channel may itself be synchronous (that is, once a messageis sent on a channel, another message may not be sent until a reply tothe first message is received).

As shown, the remote IPF module 134 or charging component 214 mayinitiate communication 902 with the flow control server 106. In someembodiments, communication 902 may be initiated when, for example, anelectric resource 112 first plugs in/connects to the power grid 114. Inother embodiments, communication 902 may be initiated at another time ortimes. The initial message 902 governed by the protocol may require, forexample, one or more of an electric resource identifier, such as a MACaddress, a protocol version used, and/or a resource identifier type.

Upon receipt of the initial message by the flow control server 106, aconnection may be established between the remote IPF module 134 orcharging component 214 and flow control server 106. Upon establishing aconnection, the remote IPF module 134 or charging component 214 mayregister with flow control server 106 through a subsequent communication903. Communication 903 may include a location identifier scheme, alatitude, a longitude, a max power value that the remote IPF module 134or charging component 214 can draw, a max power value that the remoteIPF module 134 or charging component 214 can provide, a current powervalue, and/or a current state of charge.

After the initial message 902, the protocol may require or allowmessages 904 from the flow control server 106 to the remote IPF module134 or charging component 214 or messages 906 from remote IPF module 134or charging component 214 to the flow control server 106. The messages904 may include, for example, one or more of commands, messages, and/orupdates. Such messages 904 may be provided at any time after the initialmessage 902. In one embodiment, messages 904 may include a commandsetting, a power level and/or a ping to determine whether the remote IPFmodule 134 or charging component 214 is still connected.

The messages 906 may include, for example, status updates to theinformation provided in the registration message 903. Such messages 906may be provided at any time after the initial message 902. In oneembodiment, the messages 906 may be provided on a pre-determined timeinterval basis. In various embodiments, messages 906 may even be sentwhen the remote IPF module 134 or charging component 214 is connected,but not registered. Such messages 906 may include data that is stored byflow control server 106 for later processing. Also, in some embodiments,messages 904 may be provided in response to a message 902 or 906.

Site Power Flow Manager

Modern electric vehicles benefit in a variety of ways from a centrallycontrolled smart charging program where a central server coordinates thecharging activities of a number of vehicles. While many such smartcharging programs may be operated by electric utilities to controlelectric vehicles over a wide area, many of the benefits of a smartcharging program can be realized at a local level by the operator of afacility operating in isolation from the any other entity. In a placewhere multiple plug-in vehicles may park and connect to the grid, it isvaluable to have site-level charging management.

As shown in FIG. 10, the charging process of electric vehicles 1000 ismanaged by a site power flow manager 1010 at the site-level 1020.Site-level charging management is an important feature at charginglocations where multiple plug-in electric vehicles 1000 may park andconnect to the grid 1030. Such locations/sites 1020 may include publicor private parking lots, or the base of operations for a fleet.

There are a number of benefits for managing the power flow at thesite-level. Having control over the flow of power is useful when, forexample, the grid connection 1030 at the site 1020 is not capable ofsupporting every electric vehicle 1000, and/or other devices on site,that is simultaneously drawing power. In some instances, the wiring tospecific charge points 1040 at the site, or to banks of charge points atthe site 1020, may not be capable of supporting every vehicle 1000drawing power at the same time. Many sites are subject to demand chargesbased on peak power draw during a time period (e.g. month), so avoidingpower spikes can also save money. Furthermore, power usage can be tunedto the specific electric rate structure of the site.

A site power flow manager 1010 could address these issues, inter alia.Providing a power flow management system at the site-level allowsimportant information to be taken as input, including but not limitedto: electrical meter data for the site 1020 as a whole, and/orelectrical meter data for specific charge points 1040 or banks of chargepoints. In addition, the system can consider information from devices,such as plug-in vehicles 1000, at the site that are connected to theelectric grid 1030. Such information might be transmitted in a varietyof ways, including by a power-line carrier or a wireless means. Thisinformation may include a unique identifier, resource type, currentstate of charge, and max power in/out levels. Further, the system canreceive information about the electric rate structure of the site, sandinformation about the electrical topology and power limitations ofvarious circuits within the site. A connection to a power flow manager1010 operates at a higher level of the grid topology, i.e. at thesubstation level or the control area level, so that the site power flowmanager 1010 can receive information and also respond to requests, suchas a demand response event, a reserves call, renewable resourcefollowing, or system regulation. In one embodiment, the site power flowmanager 1010 and the higher level site controller can have priorityrules, e.g. not overloading local circuits takes priority over remoterequests.

A site power flow manager 1010 can analyze the current, and thepredicted future, state of the world. In doing so, the site power flowmanager 1010 can make various determinations, including whether or notto allow certain devices/vehicles 1000 to draw power. In addition, sitepower flow manager 1010 can request that the devices/vehicles 1000provide power, and further control the power levels of thedevices/vehicles 1000. These decisions could be made within constraints,such as not overloading a circuit or going over a certain total powerdraw. Such constraints may be performed, as in one embodiment, withprioritization, such as optimizing to get power to certain devicesversus others. For example, the site power flow manager 1010 may chargevehicles 1000 that are at the lowest state of charge, that have beenplugged in the longest, or that have priority for recharge. In anembodiment, the site power flow manager 1010 may allow for optimizingwith regard to the overall site electric cost minimization or total costminimization, or to recharge in the greenest, most efficient meaner.

Decisions made by the site power flow manager 1010 can be carried out inseveral ways, including controlling relays to open or close certaincircuits. In addition, the site power flow manager 1010 can communicatewith smart charging points 1040 or smart banks of charging points 1040to control certain circuits or devices 1000 on those circuits. The sitepower flow manager 1010 may also communicate with the devices 1000 togive them a request or command for their power flow behavior, such astelling a vehicle 1000 to charge at half power or to recharge in anefficient manner. Such communications may traverse via a smart chargingpoint 1040 or bank thereof. The site power flow manager 1010 may belocated at the site 1020 being managed, but can also located remote tothe site 1020.

FIG. 11 illustrates the site-level charging of electrical devices by apower flow manager 1110. The power flow manager receives site-levelinformation 1120, and makes power flow decisions based on the site-levelinformation 1130. In addition, power flow to the electrical devices ismanaged by the power flow manager 1140, such that the power flow managerresponds to requests including demand response event, reserves call,renewable resource following, or system regulation.

Meta-Optimization Across Multiple Power Flow Management Strategies

Managing one or an aggregation of power resources (such as load,generation, storage, plug-in vehicles), power flow manager can use thecombined capabilities of the assets under its control to implement avariety of beneficial services. These services may include regulation,spinning reserve, and/or peak avoidance. Regulation involves increasingor decreasing the load present on the grid in real time in order tomaintain balance between power production and power consumption in theentire grid. Spinning reserve provides the ability to quickly make up alarge amount of missing power after the failure of a generation ortransmission asset within the grid. Peak avoidance results in reducingpeak power consumption for the day, which is typically the mostexpensive power for the utility to provide.

There are many other similar services, such as to provide capacity or toprovide renewable generation following. As the power flow manager mayuse any number of different strategies to decide how to dispatch theresources under management, it will be understood by those skilled inthe art that other strategies, and combinations thereof, may beimplemented in various embodiments. In one embodiment, the power flowmanager may be a site power flow manager 1010, as shown in FIG. 10.

Such services provide a substantial cost savings to an electric utility.In many circumstances, it is also possible for a utility or otheroperator to sell these services through an energy market. While each ofthese services have very distinct characteristics from the perspectiveof the electric utility, the services are each implemented infundamentally the same way on the power resource endpoint. That is, byselectively flowing power in to or out of the power resource in responseto commands from the central power flow manager.

Because the same pool of resources can be used to implement each of thepossible services, a conflict arises. As an example, If an entirepopulation of electric vehicles is committed entirely to regulationservices, that population not be able to fully participate in a peakavoidance program. Because the relative costs and benefits of thevarious services change over time, it is undesirable to simply pick themost valuable service and commit all the assets to it all of the time.

Given a set of such strategies, a meta-optimizer decides which strategyto use at appropriate times. The meta-optimizer may be located withinthe power flow manager. The meta-optimizer determines which resourcesare to be used in implementing a strategy. The determination may bebased on a variety of factors, such as maximizing value generated and/orminimizing environmental impact. In an embodiment, the meta-optimizerchooses the strategy that is likely to generate the most value for agiven time period, e.g. the next hour. The implementation may have avalue function associated with each strategy, and then take the maximumvalue across all strategies.

The decision may vary by grid topological location. For example, if agiven feeder is overloaded, the best decision for resources on thatfeeder may be to reduce the load, even if elsewhere on the grid adifferent strategy or action may be best.

The decision may also take into account multiple component requirements.For example, in managing plug-in vehicle recharging, it may be desirableto get vehicles recharged in a timely fashion, while also maximizingvalue created through other services provided.

In one embodiment, the decision may be based on predictions about thefuture. For example, it may be worth a certain amount at hour N to takesome action, such as charging plug-in vehicles to provide downregulation. However, if that means the resources might be unavailable athour N+1, when the resource may be worth more than at hour N, then themeta-optimizer might delay the action so that the resource is availableto provide more value.

FIG. 12 shows an embodiment of a method for managing power flow byoptimizing multiple power flow management strategies includingcoordinating charging activities 1210 and controlling power flow service1220. A meta-optimizer can choose a power flow management strategy andan electrical device 1230 such that the power flow manager may implementthe power flow management strategies 1240.

Avoiding Power Spikes During Energy Management Failures

Historically, utilities had to depend on the independent and randomnature of electrical loads on the grid. While an individual electricalload is unpredictable and can be switched on or off at any time, eachload is only a small part of total power consumption. The large numberof individual loads on the electrical system provides a form ofsmoothing. Electrical consumption increases and decreases over time, butthe overall change fluctuates along a somewhat predictable curve andpower companies are able to adjust power production to matchconsumption.

In distributed energy management systems where communications are not100% reliable, it is important that no loss of communications betweenthe elements of the system or unexpected system controller failure causeunexpected system behavior. One particular behavior to be avoided is anunexpected, coordinated action across distributed resources that resultsfrom a failure mode. For example, when a controller suffers a failure,it could be detrimental to the electrical grid if all distributedresources started drawing power from the grid simultaneously.

The introduction of a smart charging or energy management system causesotherwise isolated loads to potentially operate in concert. This createsthe possibility of adverse coordinated action in the event of systemfailure. In particular, if each electrical load is designed to revert toa maximum energy consumption level in the case of communications loss,then a failure of the management system may result in an instantaneousand coordinated spike in electricity demand. When the population ofcontrolled devices is sufficiently large, the spike in demand can exceedthe utility's capacity for rapid adjustment and result in a blackout.

An example of a failure mode includes failed communications betweenindividual resources and the master controller or controllers.Communications can also fail between a controller and some or all of theresources. In addition, a controller or a set of controllers can fail ina non-network related way that renders such controllers incapable ofcommunicating with the resources. A failure mode may also be a designdefect shared by a large population of resources causing the populationto simultaneously lose communications capabilities when an unexpectedevent occurred.

In the case of any failure mode, the system behavior should bepredictable and non-disruptive. To prevent disruptive impacts on thegrid as a whole, endpoints normally controlled by a central energymanagement server may employ a variety of safe failure modes. A systemfor maintaining predictable behavior may include a distributed resourcewith various capabilities, including the ability to receive/enact asequence of commands to be executed at one or various points in time.

An example of a safe failure mode includes maintaining stable(non-changing) behavior for a defined period of time around a failureevent. For example, after communications is lost, an isolated EVSE cancontinue charging at the rate last specified by the charge managementcontroller. After some period of time, the EVSE may slowly transition toa different autonomous strategy.

Another safe failure mode includes executing a pre-arranged behavior inthe event of a failure condition. As an example, if a group of EVSE'swas connected to a electrical circuit that was only capable of providing70% of the combined maximum power draw of the group, each EVSE could bepre-programmed to operate at 70% of capacity in the event ofcommunications failure.

Yet another safe failure mode includes executing state transitions inpre-arranged behaviors at the determined time offset by a randominterval of time. As an example, EVSE's that are off when communicationsfail could wait a random amount of time between 0 and 30 minutes beforepowering on. This random startup causes the increase in powerconsumption to be spread over time, allowing the utility the opportunityto respond.

A safe failure mode may also include using predictions about resourcebehaviors, such as the comings and goings from the system, to furtherenhance the estimate of the state of the world. As an example, if anEVSE is normally commanded to consume power along a curve (to harmonizewith grid conditions), the EVSE could be programmed to follow type-basedtypical curve in the absence of communications. Since the central smartcharging system would know the curve the detached EVSE was following,its behavior could still be input in to the charge managementalgorithms.

FIG. 13 illustrates an embodiment for managing power flow using safefailure modes including coordinating charging activities of electricaldevices 1310 and detecting a system failure event 1320. The power flowmanager implements a safe failure mode 1330 that provides predictableand non-disruptive system behavior.

Generation-Stack-Aware Dispatch of Resources

One potential goal of a distributed energy management system is todispatch resources to minimize cost. A basic cost reduction strategy isto reduce electricity consumption when electricity prices are high. Thisbasic strategy reduces the cost of electricity consumed by the endpointsunder active management.

A more advanced strategy could manipulate the electricity consumed bycontrolled endpoints in a way that impacts the market price of power.Such a system can reduce the cost of providing power to all deviceswithin a utility's service area, not just those under active management.

In many regions, power production is managed by separate entities fromthe utilities responsible for distribution. Utilities purchaseelectricity from Power producers, and re-sell it to their customers.

Often, the transactions between power producers and distributionutilities take place in formalized market. Such a market typicallyoperates as a single price auction. In such a market, each powerproducer states the price at which they are willing to provide power,and power production is allocated to the cheapest producers first,moving up the stack to more expensive produces until sufficient powerhas been obtained. The last (highest) price selected set the price thatall power producers are paid.

Each type of generation asset in an energy generation system, such asthe electrical grid, has a marginal cost. Generation assets aredispatched in the order of increasing marginal cost. The most expensivegenerator dispatched at any time sets the cost basis for energygeneration.

Different types of power plants have sharply different marginal costs ofoperation. For example, Hydroelectric is often much cheaper than gasturbines. As a result, there may be a sharp increase in the cost ofelectricity as available hydro is exhausted, and the gas turbines begincoming online.

At times, a distributed energy manager can remove enough load from thesystem to eliminate the need for higher cost generation, therebydecreasing the total cost to provide service.

The distributed energy manager can minimize the total daily cost toprovide energy generation by forecasting total system and dispatchableload. The distributed energy manager schedules dispatchable load to drawpower from the grid at times that will minimize cost based on theavailable generation stack. Altering the total price of power paid has alarger financial impact than the amount paid specifically for automotivepower. Also, moving the market may be easier at one time of day thananother. As a result, dispatchable load will not always be scheduled tothe lowest-cost time of day, but rather when it will have the mostbeneficial overall effect to the utility.

Further, the generation stack can change from region to region, and loadprofiles and consumption can change daily. Therefore, the present methodwill produce different dispatch patterns in different regions.

FIG. 14 shows an embodiment of managing power flow using generationstacks of power production to reduce cost of providing power toelectrical devices. Charge activities are coordinated by a power flowmanager 1410. A power production stack is controlled the power flowmanager 1420 such that the power production stack orders availablepower. Based on a cost reduction strategy, a dispatchable load isremoved 1430. The dispatchable load is listed in the power productionstack.

Business Model of Selling Aggregated Power Resource Management Servicesto Power Generators or Others

Power resource management services include aggregating the following:plug-in vehicles, thermostats, residential or commercial/industrialload, or fixed energy storage. Such services provide regulation,reserves, load shifting, renewable resource following, or peakavoidance. A power flow manager is able to provide a variety of servicesthat can improve the stability of the electric grid. For example,electricity consumption of distributed resources can be increased anddecreased as necessary to absorb the differences between electricityproduction and consumption on the grid.

Customers for aggregated power resource management services includeelectric utilities, ISOs, and TSOs. Such entities are primarilyresponsible for the stability of the grid. But aggregated power resourcemanagement services may be sold to various types of power generators.

Some classes of electricity generation suffer from a high degree ofintermittency, meaning that their power production is irregular. Bybundling this irregular power production with the smoothing/stabilizingabilities of aggregated power resource management assets, it is possibleto produce a higher grade of wholesale power, which may be more easilysold in energy markets.

In one example, a wind farm is the buyer of aggregated power resourcemanagement services. Wind farms are susceptible to fluctuations in thesupply and demand of energy. For example, prices for energy may dropdrastically when the amount of wind is great, or unexpectedly high. Inaddition, wind farms may be temporarily disconnected from a grid whenthere is not enough transmission or other capacity to absorb the power.

Economical issues resulting from such instability in the supply ordemand of energy can be effectively addressed by providing owners ofintermittent renewable generation with aggregated power resourcemanagement services. Power generators may increase their net load fromthe aggregated power resources when there is a large and/or unexpectedlyhigh amount of wind, and decrease net load with there is a small and/orunexpectedly low amount of wind. [00231] In an embodiment, powergenerators can use aggregated power resource management to smooth suddenramping events in power output, or to firm the power output to a desiredlevel. The sum of power generation plus net load from the aggregatedpower resources can be made constant, or less susceptible to changes inthe supply or demand of energy.

As a result, power generators such as power plants may retain the valueof the energy they create. Such an integration allow the operator of thegeneration asset to take direct action to address the intermittencyissues associated with their type of generation. In some markets, thismay be far more desirable than waiting for other parties to provide suchservices through the marketplace.

AGC Virtualizer

An attribute of the electrical grid is that power production must alwaysbe closely matched to power consumption. As such, electric utilitiespredict power consumption in advance using a variety of techniques inorder to schedule power production to match consumption. Because thesepredictions are never entirely accurate, the electric utility is leftwith a shortfall or surplus of produced electricity.

To address this mismatch between predicted and actual power consumption,utilities arrange for some power generation plant to operate in aregulation mode. This is sometimes called system regulation, orfrequency regulation. In regulation mode, the power output of a powerplant can be increased or decreased in near real time. In the event of apower surplus, the utility orders the power plant in regulation mode todecrease power production. In the event of a power shortage, the utilityorders the power plant to increase power production. Not all powerplants are capable of operating in this mode, and the power plants thatare often incur increased costs while in this mode. Issues such as fuelefficiently and mechanical stress must be accounted for when figuringthe cost of regulation mode.

A power flow manager can provide system frequency regulation viaAutomatic Generation Control (AGC) commands. As such, the system mayappear to behave as an ISO/TSO or a grid operator, such as a powerplant, even though it is not actually a power plant. The power flowmanager coordinates the behavior of power resources, such as thefollowing: load, generation, or storage. The power resources can includeplug-in vehicles, fixed energy storage, loads such as HVAC, or otherdevices. The AGC commands can be translated by the power flow managerinto commands to specific devices, or sets of devices within its pool,in order to achieve aggregate behavior across the set of resources thatmatches the AGC request.

In an embodiment, the AGC command can be transmitted to all powerresources. The magnitude of the command can be divided up among thepower resources in proportion to the power range of each resource,accordingly to one embodiment. For example, a command for 1 MW of downregulation can be divided up such that a device with a 2 kW potentialpower swing between max power in and max power out would be asked toprovide half as much contribution as a device with a 4 kW potentialpower swing. More complex schemes can optimize dispatch based on avariety of factors, including: minimizing communication to resources;fairness; maximizing ability to provide services in the future, e.g. notfilling up a plug-in vehicle that can only be charged; or, resourceowner preferences or requirements.

AGC allows for regulation in two directions. Up regulation is a requestfor additional power, while down regulation is the request for areduction in power. A power flow manager can implement bi-directionalregulation (both up and down) using only power resources that arecapable of unidirectional power flow. This is accomplished by setting apopulation of power resources to consume power at a rate less than theirmaximum (e.g. 50%), and then adjusting power consumption up and down inaccordance with AGC commands. During periods of power shortage(resulting in up regulation requests), the power resources could curtailenergy use and/or increase energy output. During periods of powersurplus (resulting in down regulation requests), the power resourcescould increase energy use and/or decrease energy output relative totheir initial rate.

FIG. 15 shows an embodiment of power flow management using AGC commandsto control power resources 1510. Power regulation is apportioned to thepower resources 1520. An AGC command, which requests an apportionedamount of the power regulation, is transmitted to a power resource 1530.

AGC For Resources Beyond Generation

Automatic Generation Control (AGC) can be utilized to control powerplants so that they may provide system frequency regulation. In anembodiment, a power plant might be scheduled to provide 30 MW of powerduring a certain hour, while also being available to provide 10 MW ofdown regulation and 20 MW of up regulation during that hour. As such,the plant output might vary anywhere from 20 MW to 50 MW. In anembodiment, AGC typically transmits a power level set point within thisrange, e.g. 37 MW, or may send relative power request, i.e. increasepower or decrease power relative to the current level.

Given a load or energy-storage based power resource, or an aggregationof such power resources, system frequency regulation can also beprovided by adjusting the net balance of supply and demand for energy.Energy storage in discharge mode can output power much like a generationplant. Load, or energy storage in charge mode, can consume power likenegative generation. When a number of vehicles/resources aregrid-connected and charging, an up regulation request can be serviced bytemporarily reducing the rate of vehicle charge. Additionally,generation based power resources can be part of an aggregate of otherload or energy-storage based power resources.

In one embodiment, AGC systems and protocols can be extended to handlepower level set points that can be negative. As such, the power flowmanager receiving the request can treat negative values as requests forenergy consumption, and positive values as requests for energyproduction. When the AGC system does not support negative numbers, theentire power range can be shifted to start at zero, such that the shiftamount becomes a separate load amount within the system. For example, apower range of −5 MW to 10 MW can be shifted to be 0 MW to 15 MW withthe offset amount becoming a separate load amount of 5 MW.

FIG. 16 illustrates an embodiment of power flow management using AGCcommands to control power resources 1610 where a power regulation rangefor a power resource is determined 1620. An AGC command based on thepower regulation range is transmitted to the power resource 1630.

Intermittent Generation Smoothing and Leveling

Intermittent generation resources, such as wind or solar, can sufferfrom sudden ramping up or down in output, as well as somewhatunpredictable output levels over time. For example, the wind speed ordirection can shift rapidly or a cloud can temporarily obscure the sunover a solar generation asset. Since power production must always beclosely matched to power consumption, it is very difficult to integrateunreliable generation resources in to the grid, particularly as thepercentage of power being provided by such resources increases in thegeneration mix.

In some situations, utilities are forced to provision conventionallyfueled standby power generation assets to provide backup to theintermittent generation resources. For example, natural gas turbines areoften used in this way. Other rapidly adjustable generation such ashydro may also be used to provide this firming of intermittentgeneration. This substantially increases the real cost of renewableenergy sources. To address these issues, a single power source or anaggregated collection of power resources can be controlled. Suchresources may include load, generation, or storage.

In the case of unexpected drop-off in electricity production, managedpower resources can reduce their electricity consumption. Powerresources capable of reverse energy flow may also contribute electricityback to the grid. In the case of an unexpected spike in electricityproduction, managed power resources can consume the surplus electricityby increasing their rate of energy consumption, or by other means. Acollection of power resources could be managed using at least twodistinct strategies: smoothing and leveling.

In a smoothing method, the rate of change of power output can belimited. When a sudden increase or decrease in power production occurs,the managed power resources can be used to spread this sudden changeover more time. As an example, a sudden drop-off in wind production from10 MW to 0 MW could be spread out over 20 minutes (using stored power,deferred charging, and other shifts in net power draw), affording theutility additional time to locate replacement power sources or otherwiseaddress the shortfall.

In a leveling method, the overall contribution of the generationresources to the grid can be balanced by the power resources to providea desired level of net generation. In an embodiment, such methods areused when output from a wind farm falls below a desired level. Acollection of aggregated resources, such as plug-in vehicles, aredispatched to absorb the power drop. Some of the plug-in vehicles arerequested to stop charging, or to charge at a lower rate. With asufficiently large and capable collection of distributed powerresources, leveling could increase the reliability of renewables to thesame level as conventional power sources.

In an embodiment, leveling may be more valuable than smoothing to anutility or other operator. However, leveling may require a large amountof reserve capacity relative to the amount of renewable energy beingmanaged. Smoothing can provide substantial benefit while requiring asmaller population of distributed energy resources.

FIG. 17 illustrates an embodiment of power flow management that detectsa change in an intermittent power flow 1710 and implements a power flowstrategy in response to the change in the intermittent power flow 1720.The power flow strategy may be a smoothing strategy or a levelingstrategy.

Mobile Resource Locator

Referring back to FIG. 1, the exemplary power aggregation system 100also includes various techniques for determining the electrical networklocation of a mobile electric resource 112, such as a plug-in electricvehicle 200 as illustrated in FIG. 2A. Electric vehicles 200 can connectto the grid 114 in numerous locations and accurate control andtransaction of energy exchange can be enabled by specific knowledge ofthe charging location. Some of the exemplary techniques for determiningelectric vehicle charging locations include:

-   querying a unique identifier for the location (via wired, wireless,    etc.), which can be:-   the unique ID of the network hardware at the charging site;-   the unique ID of the locally installed smart meter, by communicating    with the meter;-   a unique ID installed specifically for this purpose at a site; and-   using GPS or other signal sources (cell, WiMAX, etc.) to establish a    “soft” (estimated geographic) location, which is then refined based    on user preferences and historical data (e.g., vehicles tend to be    plugged-in at the owner's residence 124, not a neighbor's    residence).

Location Determination Using a Network Fingerprint

The presently disclosed systems and methods can solve the problem ofdetermining the location of a device with respect to a known location onthe electrical grid or a known physical location (e.g. my home, myoffice) associated with a location on the electrical grid. Traditionalapproaches of using the Global Positioning System (GPS) or cellulartower based Location Based Services (LBS) are not sufficient.Limitations in GPS and cellular resolution make the precisedetermination of a location difficult, especially in cases where twolocations are overlapping or in close proximity. When two locations aretoo close to distinguish and resolve their locations using GPS and/orcellular information, or in cases where GPS and cellular information isnot available because of the lack of a transceiver or the lack ofsignal, the device described herein uses a collection of othercommunication based information to construct a network fingerprint of aknown location that is subsequently used to determine whether a deviceis at a previously known or unknown location.

In one embodiment, the disclosed methods determine whether an electriccar, or other electrical equipment such as a charging station that maybe semi or completely mobile, has moved from one known location toanother or otherwise left a known location. This is crucial whendetermining billing related matters; for example, when deciding whetherto bill my home or my office for the electric power used or produced. Itis also important to have knowledge about which devices are located on anetwork when establishing the overall load characteristics of a givenarea of the grid. In one example, such knowledge is useful indetermining whether charging a device affects, or will affect, theoverall load of my home neighborhood or my office neighborhood.

To address the issue of location resolution, a device may contain one ormore communications adapters, such as Ethernet, Wi-Fi, ZigBee, Cellular,LBS, or GPS. The device may use some or all of these communicationsmediums in a combination of active or passive modes to extractinformation that is unique to a given location. Various techniquesfingerprinting devices on a network may be combined to construct anoverall fingerprint of the surrounding network as a whole.

Once a network location fingerprint is collected and stored it may beassociated with a known location (e.g. home, or office, or parking lotspace #12), or it may be assigned an otherwise random locationidentifier. The fingerprint may be stored in a database for later usewhen trying to determine a device's location.

The disclosed system can also take into account the dynamic nature ofsuch information. A portion of the fingerprint may be expected to changeover time. For example, the list of network peers may change as newpeers are added or removed from the network. The MAC address of devicesmay change as they are replaced with new hardware. Host operating systeminformation collected in IP stack fingerprinting may change as operatingsystems are upgraded. As such, the fingerprint of a location may changeover time and the database can record the last fingerprint. The databasemay also record the entire history of fingerprints of a location incases where the variation over time is itself useful in identifying thelocation. For example, a given home location may have three networkpeers in the evenings while various people are home from work with theirnetworked laptops and phones, but may have only one peer during theworkweek while they are at work. Depending on the time that the networklocation fingerprint is compared, this sort of dynamic information canbe used to resolve the location name.

Pattern matching can be used to match one location fingerprint againstanother. Based on the statistical nature of the fingerprint, thedisclosed system is capable of making a location determination in thepresence of partial or changing fingerprints by applying any number ofstatistical methods, such as regression analysis, logistic regression,Bayesian, pattern matching, or ad hoc weighting of various parts of thefingerprint. For example, the likelihood that a given location willreplace the communications gateway that a car would connect to (and thusa change in the MAC address present in IP traffic from the gateway) isprobably low in comparison to the probability of adding or removing ofpeers to the same network.

In an embodiment, the disclosed method uses a process by which a deviceconnected to a network can query network peers and collect and store aset of identification information, such as MAC address, IP address, andtrace routes. The method may utilize other various pieces of informationto construct a fingerprint of the device's current location such as pinglatencies to gateways, other network peers, cell tower information, orGPS information. As such, the method constructs a location fingerprintthat is the aggregation of various sources of information, and mayfurther use a statistical model weighting the relevance of the variouspieces of information. The information can be stored on a server or thedevice.

When a device subsequently performs the fingerprint process, the devicecan subsequently detect whether the device has changed locations bydetecting differences in some or all of this set of information. Upondetecting that the device has returned to a known location, or that thedevice is at a new location, the device or a server can take certainactions. Such actions may include: notifying a user, notifying anotherserver, initiating a configuration process, or operating in differentmodes.

According to an embodiment, a user plugs in a device to their homenetwork, and the device scans for and records the MAC addresses of theuser's router, home PC and printer. The device transmits, thisinformation to a server, such that a fingerprint is, associated with thelocation. The user may move the device to a new location, e.g. theuser's office. The device detects a different fingerprint from the MACof a new router, and several dozen work computers. Another informationrelating to the new location is stored in the server so that thefingerprint is associated with the location. When the user returns thedevice to the home network, the device recognizes it is at home. Thedevice can recognize a location even if some, but not all, of thefingerprint has changed. For example, a printer may no longer bepresent.

FIG. 18 shows an embodiment of fingerprinting a local network for apower management system. Network information from devices, such aselectric vehicles, is collected 1810 in order to generate a networkfingerprint 1820, which is stored 1830 in a database. As shown in FIG.19, according to an embodiment, a change in the location of a device isdetected 1910 and compared with a network fingerprint 1920 in order todetermine 1930 the location of an electric vehicle.

Accurate System Metering Via Statistical Averaging

Metering information for an aggregate power system from the endpointsrequires a meter at each endpoint. A potential cost reduction for suchsystem is to reduce the accuracy of each individual meter. Building amodel for the meter error for each type of meter in a system provides anupper bound on system accuracy. Any bias, or offset from zero, can beremoved from the system level calculation by utilizing such a model.Additionally, the standard deviation of the meter error can becharacterized.

In an embodiment, the meter population can be characterized as 1,000meters in the system being uniformly distributed over the range of +/−2%with a standard deviation of 1.15. The total system error is defined bythe sum of the meter error terms. This error can be estimated bycomputing the standard error on the sample mean of the samplingdistribution using the formula stderr=stdv/sqrt(N) which provides astandard error=1.15/sqrt(1000)=0.0364 in this embodiment. To maintain acertainty of 99% on this estimate, the error percentage estimate may bemultiplied by 3 because, under a normal distribution, 3 standarddeviations covers roughly 99% of the samples. This results in 0.1091%for the currently presented embodiment.

The implication of this observation is that even if our meter error isuniformly distributed within +/−20% with only 1,000 meters, thedisclosed system can still achieve a measurement accuracy of +/−1.1%.

Aggregate System Power Flow Inference

A power flow management system is responsible for producing an estimateof the aggregate power flow to or a from a set of devices that areparticipating in system. By collecting individual power flowmeasurements from endpoints participating in the power flow managementsystem and aggregating those measurements, the system produces anestimate for the aggregate power flow of the devices.

For the purposes of this disclosure, ESVE or should be understood to beElectric Vehicle Service Equipment, which is herein, defined as a devicethat is a permanently installed piece of electric vehicle charginginfrastructure that serves as an electric vehicle outlet. This type ofequipment may include an energy meter.

For the purposes of this disclosure, aggregate power flow should beunderstood to be the sum of the power flows in a set of individual,distributed devices that are under the management of a power flowmanagement system.

For the purposes of this disclosure, error bounds should be understoodto be a limit on the magnitude of the error in the estimation of anaggregate power flow my a power flow management system. The error boundson an aggregate power flow are specified with a level of confidence.

The devices that measure power flow at the endpoints of the systems(e.g. vehicles, homes, HVAC, EVSE) have non-ideal levels of measurementaccuracy. That is, the power flow reported by the devices is the sum ofthe actual power flow and some amount measurement error (the error couldbe positive or negative).

By characterizing and modeling the measurement error of a class ofdevices, it is possible to produce error bounds for the power flowmeasurement of a population of devices by considering the device errormodel and the number of devices included in the computation. [00281]FIG. 20 illustrates a method for inferring an aggregate power flow fordevices attached to a power management system. A plurality of power flowmeasurements are received 2010 from a plurality of devices, each devicebeing associated with a power flow, each of the devices being capable ofmeasuring the respective device's power flow within a measurement error.The plurality of power flow measurements are aggregated 2020, producingan aggregated power flow measurement.

In one embodiment, the power flow aggregate for a set of devices can becomputed as the sum of the individual measurements that are a part ofthe aggregate measure.

In one embodiment, the error bounds on an aggregate power flowmeasurement of a set of endpoints connected to a power flow managementsystem can be additionally be computed. Making an assumption that thepower flows at each individual device are independent and identicallydistributed (i.i.d.), the standard error of the aggregate power flowmeasurement can be computed by using the statistical definitions fori.i.d. random variables. That is, divide the error bounds of eachindividual device by the square root of the number of devices in the setto compute the standard error. The error on the aggregate power flowmeasurement is then bounded by multiplying the standard error by thenumber of standard deviations desired. For example, if a 95% confidenceis desired, then the computed standard error value is scaled by 1.96(the matching quartile for the normal distribution).

Power flow estimates can be produced for the entire system being managedby the power flow management system as well as for sub-parts (portions)of the complete system. Because the error bounds can be produced by anerror model parameterized by the number of devices included in thecomputation, computing the error bounds for subsets of the devicepopulation requires adjusting the input (number of included devices) tothe error model.

By modeling the measurement error in the measurement device at theendpoint, the power flow management system can compute the error boundsfor the aggregate estimate of the power flow measurement at any point inthe power flow management system.

This approach can support any meter error model and can even combine anarbitrary number of measurement error models. If the device type thatperforms the metering is known on a per-endpoint basis, it is possibleto compute the number of instances of each device type contributing tothe aggregate estimate. These individual devices counts are then used tofeed the per-device-type model of error bounds.

In one embodiment, an error model for a set of devices of an identicaltype can be constructed. In one example of such an error model for a setof metering device, each individual device of a particular type isguaranteed to have all measurements within +/−N % of the true value.

In one embodiment, the error bounds of a subpart of the endpoints in apower flow management system can be computed. If it is needed to computethe error bounds for a subset of the endpoints under the management ofthe power flow management system, the standard error is computed bydividing the error bounds of an individual device by the square root ofthe number of devices in the subset. The error on the aggregate powerflow measurement is then bounded by multiplying the standard error bythe number of standard deviations we would like to capture in ourestimate.

In various other embodiments, different error models are combined. Onemethod for combining multiple error models (i.e. multiple types of powerflow measurement devices) in the same power flow management system is tocompute the weighted average of the error bounds for each set of devicesdescribed by a single error model where the weight is the percentage oftotal power measured by that set of devices.

Inferring AC Power Flow From DC Measurements

In a power flow management system, each endpoint device is responsiblefor reporting its own power consumption and production. In many cases,the endpoint device has sensors for measuring the Alternating Current(AC) power flow through the device (i.e. how much power the device istaking/delivering from/to the grid). However, some devices may not havethe ability to produce accurate sensor data for the AC power flow of thedevice.

In cases where the device has other sensors that produce someinformation about the state and behavior of the system, it is possibleto build an inference model for the AC power flow given the informationfor the other sensors. For example, in a battery charger, there may notbe AC metering sensors, but their may be sensors that measure thebattery's DC voltage and the DC current being used to charge it. If thisadditional information is available, then the battery charging devicecan be characterized such that accurate AC metering information can beinferred from the DC sensor readings.

FIG. 21 illustrates a method for inferring AC power flow in a devicefrom DC measurements. A device having at least one DC power flow sensoris augmented 2110 with at least one AC power flow sensor. AC and DCpower flow is then measured 2120 over a range of operating points. Thepower flows are then used to build 2130, using at least one computingdevice, an inference model of AC power flow in the device as a functionof DC power flow, wherein the error of the model is bounded. The ACpower flow sensor can then be removed 2140 from the device. DC powerflows through the device can then be measured 2150 and used to infer2160 the AC power flow for the device using the inference model andmeasurements from the at least one DC power flow sensor.

By augmenting a single device with AC metering sensors, it is possibleto build an accurate inference model by gathering AC and DC sensorinformation for the devices, developing a model that produces theinferred AC metering outputs given the DC measurements, and bounding theerror of the model and inference outputs. With this model in place, itis possible to apply this model to the DC readings of other similardevices to infer the AC power flow information of these devices withoutaugmenting them with AC metering sensors.

If a set of devices is available, augmenting each of them with ACmetering sensors enables the construction of a set of inference modelsfor AC power flow from DC sensor information. Using this set ofinformation, it is possible to construct a single model and its errorbounds when applied to any of the devices in the set.

Consider a battery charging system that contains a battery charger and arechargeable battery. When the battery charger is plugged into the grid,it is capable of charging the battery by passing DC current into thebattery. This system is able to sense the DC (direct current) batteryvoltage and current directly. However, this system does not require orhave AC power flow sensors.

To build an inference model for the AC power flow in this batterycharging system, the system can be temporarily augmented with AC powerflow sensors. By taking readings from the DC voltage, DC current, and ACpower flow sensors for a broad range of operating points of this system,enough data can be collected to build a model of the AC power flow as afunction of the DC current and voltage.

One such model may be a linear regression that scales some constant, M,by the DC power (DC voltage times DC current) plus some fixed offset, B.Given the full set of readings for AC power, it is possible to calculatethe values of M and B to produce an approximation of the AC power fromthe DC power.

Bandwidth Minimization Techniques

A distributed energy management system must be in constant communicationwith the distributed energy resources to maintain a high level ofcertainty that the system is behaving as reported. Sending messagesbetween the energy management system and the distributed energyresources is expensive because each message has a cost associated withit. Minimizing the number of bytes sent between the system and theresources will minimize the communications cost of the system.Accordingly, the consumption of network bandwidth is reduced.

Bandwidth, as used herein, can refer to network bandwidth. Bandwidth isthe number of bytes per second of data traffic that flows into or out ofa device or control system. Devices managed by the power flow managementsystem can be any load, generation, or storage asset. Storage assets cancomprise, batteries and bi-directional power electronics such asinverters and chargers. Load assets may include water heaters, plug-inelectric or plug-in hybrid electric vehicles, water heaters, generationfacilities, or other controllable load, storage, or generation asset.

The disclosed system and methods can provide for the minimization ofnetwork traffic consumption in a system that manages the power flows toand from devices connected to a power grid. This power flow managementsystem communicates with the devices, and can be centralized ordecentralized. Through this communication, information about power flowsis communicated to devices and information about device behavior andstatus is communicated to the system.

The system communicates with the devices to instruct devices as to whenand at what rate energy should be taken from and delivered to the grid.These commands enable the devices to consume or produce energy whendoing so is deemed optimal by the power flow management system.

The instructions that are delivered to the devices by the power flowmanagement system can take many forms. One form of instruction is adirect command to flow power immediately at the requested level. Anotherform of instruction is a schedule of power flow that should be followedby the device and can take many forms. A schedule can indicate a singlepoint in time at which a power flow level should be activated. Aschedule can indicate a sequence of power flow levels that should beactivated at various times in the future. The schedule can be repeatingon a dynamic or fixed pattern, e.g. repeat a set of actions each day,each week, etc.

The devices also communicate information to the power flow managementsystem about the current state of the world at the device. Informationthat can be transmitted for the benefit of controlling power flowsincludes information about how much power is currently flowing throughthe device and in what direction, capacity information pertaining to theresource (e.g. storage state of charge, fuel level of a generator),faults and error messages, presence of a resource (e.g.: electricvehicles come and go; is the electric vehicle currently available),scheduling constraints (e.g. how long is the resource available), energyconsumption in a period (e.g. kWh consumed/produced in the last timeperiod), etc.

Sending messages between the power flow management system and thedevices requires the sending of data bytes across a network, whichconsumes network bandwidth. Because many communications costs can bedirectly measured by the number of bytes transferred to and from adevice, minimizing the transfer of bytes between the device and thepower flow management system minimizes the communications costs andconsumption of network bandwidth.

A power flow management system can perform in a more efficient mannerwhen it has complete information about the state of all of the devicesunder its control at all times. To realize this level of informationawareness requires all assets to communication all informationpertaining to the power flow management system in a timely fashion. Sucha level of information communication comes with an associated cost.

There are a number of techniques that can be used to reduce the networktraffic consumption in a power flow management system to reduce the costof communicating with the distributed assets. Such techniques includethe following: data compression, data overhead reduction,action/schedule pre-distribution, minimum change dispatch, communicationof all status changes, configuration limits on relevant behavior, andnon-time-critical information bundling. These bandwidth minimizationtechniques, and embodiments thereof, are further described below.

Data Compression. One of the techniques for minimizing bytes between thesystem and the distributed resources is data compression within amessage. Compressing the data that is sent between the power flowmanagement system and the distributed devices can reduce the totalnetwork traffic consumption.

A power flow management system that communicates with devices can sendcompressed messages to save on network traffic. One manner in which thisworks is to have both the power flow management server and the deviceuse a compression algorithm or library (such as zlib or gzip) tocompress data before transmission and to decompress data aftertransmission.

Reducing Data Overhead. In one technique, more bytes are included into asingle message in order to reduce per-message overhead. Because eachnetwork message has some associated overhead, it is beneficial to putmore data into a single message to reduce the network consumption onoverhead traffic.

A device that is part of a power flow management system may collect datafrom its sensors and internal processes. For the bits of data that arenot time critical to the system, the device can cache the data until theratio of data to overhead is less than 5%. In the case of TCP/IP, thismeans waiting until the device had gathered 1280 bytes of data beforesending. [00312] Action and Schedule Pre-Distribution. For complicatedor long sequences of actions, these actions can be pre-distributed tothe devices (or distributed one time over the network). When any of thepre-distributed actions need to be communicated, an identifier for themore complicated sequence is all that needs to be communicated. Fordispatching actions or sets of actions, pre-compute large sets ofactions can be directed using an action identifier. As such, the actionsets are coded and only the code is transmitted. While this methodconsumes memory on the client and server, bandwidth consumption isreduced.

To achieve an application-level data compression, a power flowmanagement system can define a set of compact messages that represent apre-defined set of functionality. For example, consider a device thatruns just 4 distinct schedules during its normal behavior. Rather thansend the schedule that the device should run each time the behaviorshould begin, the power flow management system can send the device eachschedule just once. Subsequent times that each of those four schedulesneed to run, the power flow management system can indicate which of thefour schedules to run (by name or ID), and a substantial amount ofbandwidth can be saved.

Minimum Change Dispatch. Another technique for minimizing bytes betweenthe system and the distributed resources includes dispatching resourcesin a way that minimizes the total state change on a per-resource basiswithin the system. In one example, as few resources as possiblecommunicate in order to effect the desired change within the system.Each time that the power flow management system needs to change thestate of the distributed devices (e.g. now there is a need for 15 MW ofpower flow in some part of the grid, where the earlier needs was foronly 13 MW), it can choose to achieve the targeted power flow by lookingfor the minimum number of changes in the system (e.g. a device that wasoff needs to be on or vice versa) that satisfies the constraint. In oneembodiment, techniques use a single bit to toggle from one state toanother, such as from off to on and from on to off.

There are many different algorithms that a power flow management systemcan use to determine which of the connected devices should be at whatpower flow level at any point in time. Should the power flow managementsystem need to revise the net aggregate behavior of the power flowmanagement system, it will likely need to communicate with some subsetof the connected resources to signal a change in behavior.

One measure of the quality of a particular set of device change ordersis how many of the resources need to be contacted to enact the change.One algorithm for achieving the minimum change set to achieve thesystem-wide power flow goal is to find resource for which a power flowchange in the required direction is possible, and to then sort thedevices by the amount of power flow they control. Starting with thedevice that controls the most power, work down the list of availabledevices until enough power has been recruited to achieve the goal of thepower flow system.

Devices Should Communicate All Status Changes. This technique does notuse application level pings. In the case of any change in device status(e.g. power level change, fuel level change by some interestingquantity, resource arrived/departed where resource may be a vehicles),communicating all such status changes eliminates the need for the powerflow management system to use application level pings (i.e. messagesfrom the power flow management system, which has the purpose of askingthe device “Are you there?”).

In one embodiment, the implemented technique provides that resourcescommunicate their departure from the system. This enables the removal ofall application level pings from the system. This also requires that theresources have the ability to maintain power for enough time after beingdisconnected that they can communicate. When there is a localcommunications controller, the controller can indicate the disappearanceof a resource to the system.

Configurable Limits on Interesting Behavior. Another bandwidthminimization technique involves increasing the tolerance limits forstate changes that require notification of the main system. Relevantinformation should be communicated to the power flow management systemin real time. The devices should support the ability to increase anddecrease the limits of interesting behavior to make the network trafficconsumption be tailor-able against responsiveness (e.g. knowing eachtime the power flow changes by 3% is more informative than if it changesby 10% but requires network bandwidth to communicate).

Non-Time-Critical Information Should be Bundled. Techniques may minimizemessage overhead by saving data that is not time-sensitive forsame-message transmission with data that is time sensitive, therebysaving the messaging overhead and enabling data compression on a largermessage. For information that is not time critical to the operation ofthe power flow information system (diagnostic data, logged data, summarystatistics, etc), the devices should gather this information in memoryand only transmit it to the power flow management system when asufficient amount of information is collected such that the portion ofthe message dedicated to overhead is small.

Various combination of the bandwidth minimization techniques may beimplemented in an embodiment. For example, devices may communicate allinteresting changes to the power flow management system and the limitsdefining interesting behavior for the device may be configurable. Apower flow system that is fully informed and frequently updated aboutthe behavior of the endpoints that are connected to it defines oneendpoint on a continuum of control and flexibility. On the other end ofthe spectrum is a power flow management system that has little or novisibility into the behavior and status of the devices connected to it.

To enable the most flexible power flow management system whileminimizing the use of network traffic, the system can establish criteriafor devices that triggers an update action of status to the power flowmanagement system. This way, only when something changes in the statusof the device does communication need to be made. Such a scheme does notwaste network traffic having devices inform the power flow managementsystem that things are unchanged from the last communication.

For example, consider a battery charging device that is connected to abattery and participates in the network of the power flow managementsystem. Once the device has connected to the power flow managementsystem and reported its power flow (e.g. 800 W), there is no need forthe device to report new information to the power flow management systemunless there is a change in status. For example, if a device isreporting the amount of power flowing into a battery that is beingcharged and the battery fills up and does not require further charging.[00324] FIG. 22 illustrates an embodiment of a bandwidth minimizationtechnique. A power flow management system, which manages electricdevices and electric power supplies 2210, communicates deviceinformation 2220 and power flow information 2230. Bandwidth reductiontechniques described above are applied to reduce network traffic 2240.

Smart Energy Protocol Translation Device

A protocol translation device may be provided that fully participates intwo or more networks using physical signaling mechanisms that arecapable of communication with each network. Messages are reformulatedmessages such that the messages can pass from one network to another.Since two relevant protocols may not be compatible, such a device passeshigh-level information as opposed to binary packets. This method isdistinct from the method used by Internet routers that simply forwardmessages from one network to another without modification.

A Power Line Communicator (PLC), such as a power line carrier, is asignaling mechanism by which a high-frequency signal is added to the ACpower line in a home or business. The high-frequency signal carriesinformation in a variety of protocols to other devices that are able todecode these high frequency signals.

The protocol translation device may include the following: amicroprocessor and power supply; physical transceivers for eachsupported communications protocol stack; a software stack capable ofdecoding messages from each of the communications protocols; and, asoftware/hardware layer that can translate, if necessary, and re-encodemessages from one communications protocol to another communicationsprotocol. Because modern home networking technologies can be wireless orPLC based, the protocol translation device need not be located near anydevice that it provides translation services for. The protocoltranslation device can be attached to any outlet in the home, such aswall outlet 204 illustrated in FIG. 2A. The protocol translation devicecan stand alone or co-reside with a device on the network.

In an embodiment, a device acts as an information bridge between twonetworks. An electric vehicle service equipment (EVSE), or a chargepoint, may communicate with an electric vehicle via the SAEJ2836application protocol over a HomePlug AV physical communication mechanismand with a home area network (HAN) using smart energy applicationprotocol over a ZigBee wireless physical communication mechanism. Suchan EVSE or charge point can implement the message translation betweenthe two networks. For messages that have equivalent meanings in bothnetworks, the EVSE can reformulate the message that comes in from theZigBee/Smart Energy network to the format of the J2836/PLC network andtransmit the message from the HAN to the vehicle.

In another embodiment, the device is a member of two different networksand the device passes messages back and forth between the two networks.The networks have some incompatibility, such as a physical layer orapplication layer. Smart energy is an application layer protocol that isimplemented for multiple physical interfaces including ZigBee andHomePlug PLC. The device can be located such that it is able toparticipate in both networks simultaneously. The device may contain thephysical equipment to be able to send/receive messages on eithernetwork, such as ZigBee for wireless and HomePlug PLC for wired. As amessage is observed on either network, the device translates the messageto the other network's physical layer. When both networks implementsmart energy, there is no need to translate the application layer aswell.

In one embodiment, an electric vehicle service equipment (EVSE) can actas such a translation device. When a vehicle has the ability tocommunicate via one protocol, and an EVSE is located where access to thecentral charge management server is provided by a different protocol,the EVSE could act as a translator between the two protocols. Such anEVSE includes complete implementations of both the hardware and softwarenecessary to support both protocols to fully decode each protocol toobtain the application level messages.

An EVSE can be connected to a vehicle using the SAE2836 protocol overPLC and can be connected to a home network using a wireless ZigBeeprotocol, according to one embodiment. The EVSE can include completeimplementations of each hardware and protocol stack. As such, the EVSEcan forward messages between the two stacks.

In an embodiment, the translation device could be physically distinct.For example, in an installation with a PLC based vehicle and a wirelessinternet access point, the translation device can be a self-containedbox plugged into a power outlet.

FIG. 23 illustrates an embodiment of a protocol translation for a powerflow management system that utilizes networks to communicate betweenelectric devices and electric power supplies 2310. A communicationsprotocol translation device reformulates messages from one protocol toanother protocol 2320 in order to transmit such messages from a networkusing one communications protocol to a network using a differentprotocol. FIG. 24 shows a communications protocol translation device2410 implemented between two networks 2420 that are connected toelectric power supplies and electric devices 2430.

Communications Utilizing Existing Hardware

Certain automotive subsystems, such as battery charge controllers,require real-time communications links to off-vehicle networks. Thecommunications hardware to provide this off vehicle link includesCellular, Wi-Fi, ZigBee, and Homeplug. Such equipment is expensive andcan be difficult to configure.

Subsystems in a vehicle are connected together over a shared bus, knownas the CAN-bus. This bus provides high-speed low-latency communicationto attached devices, but does not provide the mechanisms necessary forcommunicating with off-vehicle entities. Rather than implementcommunications hardware directly, a client subsystem issues commandsover the CAN-bus to request off-vehicle communications services fromanother “server” subsystem.

Existing subsystem in the vehicle that already possess communicationshardware can perform this server role without requiring any additionalhardware. Because the CAN-bus does not support routing or packetforwarding, it is necessary to define an encapsulation mechanism topermit the off-board communications protocol to be embedded within CANmessages.

In some circumstances, vehicle designs may include existingcommunications hardware for purposes other than charge management. Theseother uses may include emergency response and remote vehiclediagnostics. Rather than adding additional communications hardware, anelectric vehicle can make use of these existing communications modules.Such module re-use is accomplished by enhancing the software on theexisting communications modules in order to expand functionality.

Similar to modules installed via an extensibility mechanism, preexistingmodules upgraded through software can engage in smart charging throughtwo distinct mechanisms.

In one embodiment, the software upgraded communications module providesa communications path to external networks which allows vehicle modulesto participate in a smart charging program in a manner similar to thatof a vehicle that is initially equipped with a communications module.

In another embodiment, the software upgraded communications moduleincludes all smart charging logic. In this embodiment, the softwareupgraded communications module is solely responsible for participatingin the smart charging program, and then implements that program bysending primitive messages to other subsystems in the vehicle.

FIG. 25 illustrates an embodiment of communications using existinghardware with a smart charging module configured to be implemented for avehicle subsystem 2510. The vehicle subsystem is connected to a sharedvehicle-wide communications medium 2520. The smart charging module isconfigured to provide messages to a vehicle subsystem 2530.

Communication Services to Vehicle Subsystems

Modern electric vehicles benefit in a variety of ways from a centrallycontrolled smart charging program. However, the modules in the vehiclethat are capable of executing a charge management program, e.g. theBattery Management Systems Charge Controller, do not generally have theability to communicate with external networks which are outside thevehicle. To work effectively, a smart charging program requires thecentral control of an outside entity via an external network, such as aserver. This server is responsible for coordinating the chargingactivities of a large number of vehicles distributed over a wide area,such as a city.

Establishing a communications channel between appropriate vehiclesubsystems and external networks facilitates smart charging and reducethe cost of ownership of the vehicle. While most vehicle subsystems lackoff-vehicle communication, virtually all subsystems are connected to ashared vehicle-wide communications medium or bus. In many vehicles, thisbus uses the CAN-bus standard, as defined by the International StandardsOrganization (ISO) standard #11898. Over time, some new vehicle designswill transition to other vehicle-wide communications mediums, such asFlexray or other similar technologies. However, the basic principle of ashared communications medium to allow vehicle subsystems to communicatewill remain intact, and the concepts in the present disclosure will besimilarly applicable to these future communications mediums.

Rather than adding off-vehicle communications capabilities to existingvehicle subsystems, a separate module provides communication services toall subsystems on a vehicle, making these services available via thevehicle's CAN-bus. Confining the modification to a single module reducesthe cost of switching communications standards such that support can beaccomplished by installing different communications modules in differentcars.

Such a communications module includes the hardware necessary tocommunicate off-vehicle, and also connects to the vehicle's CAN-bus.Software within the communications module translates or encapsulatespackets to allow information to flow between the various vehiclesubsystems and the entities outside the vehicle.

In one embodiment, the communications module can forward messages fromthe external network, unmodified, to other vehicle subsystems. As anexample, if the external network uses the TCP/IP protocol, thecommunications module forwards TCP packets over the CAN-bus to othervehicle subsystems. Because vehicle communication busses such as CAN-busdo not natively support wide-area protocols such as TCP/IP, anencapsulation protocol is required.

Encapsulation works by defining a specific CAN message for TCPtransport. Such a CAN message includes a packet header and a packetbody. The packet header can specify the packet type to differentiate itfrom other types of CAN traffic. The packet header can also specify thepacket length, and may contain other CAN packet attributes, such asaddressing. The packet body includes the bytes of the original externalnetwork packet, such as a TCP packet.

Such a packet can be transmitted over the CAN-bus from thecommunications module to the vehicle subsystem wishing to communicate.When the vehicle subsystem wishing to communicate receives such apacket, the subsystem uses the type and size information present in theCAN packet to extract the original TCP packet. When communicating in thereverse direction, i.e. from the vehicle subsystem to the externalnetwork, the process is reversed. The vehicle subsystem places a TCPpacket within a properly formatted CAN packet and transmits it over theCAN-bus to the communications module. The communications module extractsthe TCP packet and transmits it over the external network.

In an embodiment, the communications module entirely decodes messagesreceived from the external network, and re-encodes the messages asCAN-bus messages. As such, the communications module extracts the actualintended purpose of the remote message, and transmits a new messageacross the vehicle's CAN-bus.

As an example, the communications module may receive a packet across theexternal bus with the command specifying the current price ofelectricity. The communications module transmits a CAN-bus message tothe appropriate subsystems indicating the current price of electricity.Since the communications module is fully and completely decoding andencoding each message in each direction, it is not necessary for theexternal network messages and the vehicle-internal CAN-bus messages tobe similar in any way.

A communications module can include the following components: a centralprocessing unit (CPU) with sufficient power to run the appropriatesoftware; a CAN transceiver, or transceiver for an alternate in-vehiclecommunications network; an external communications transceiver for oneor more external communications networks; a software stack capable ofwrapping high level communications packets in a CAN header, for packetsentering the vehicle, and removing a can header, for packets leaving thevehicle; software capable translating messages from a remote networkformat to the local CAN format; and, software capable of thebonding/provisioning process required by the specific externalcommunications protocol.

FIG. 26 illustrates an embodiment of communication services to vehiclesubsystems. A CAN transceiver is connected to a CPU in a vehicle and toan external bus, which is connected to a vehicle subsystem 2610. Asoftware stack is connected to the CPU for augmenting CAN headers forpackets 2620. Software is configured to translate messages from a remotenetwork format to a CAN format 2630. Software is also configured for aprovisioning process of external communications protocol 2640.

Vehicle Power Systems Control Extensibility System

Electric and plug-in hybrid electric vehicles benefit greatly fromon-board charge-management controllers. Such controllers can harmonize avehicle's electricity consumption with the needs of the power grid.However, price-sensitivity time-to-market concerns, or a lack ofstandardization, can preclude the factory installation of these chargemanagement controllers.

It is desirable that vehicles without factory-equipped chargecontrollers have the capacity to be upgraded with an after-marketcontroller. A vehicle can be upgradable by providing a physical andsoftware interface to allow the installation of a charge controller.This interface may include: a physical interface to the vehicle'sCAN-bus, via an electrical contact plug; a standardization of softwaremessages that are to be sent over the CAN-bus to control charging; and,a physical location for the charge controller to reside, where the CANinterface plug must be located.

Vehicles may be sold without the ability to communicate with off-vehiclenetworks or systems, and therefore without the ability to coordinatetheir charging behavior with a central authority or server. A vehiclemanufacturer that recognizes the benefit of charge management may opt tonot include charge management, due to reasons such as price sensitivity,time-to-market concerns, or a lack of standardization. In thesesituations, it is beneficial for vehicles to be easily upgradablethrough the installation of a communications module or charge managementmodule. Such upgradability can be, managed by clearly defining thephysical, electrical and software interfaces between a communicationsmodule and the vehicle.

The mechanical interface may include a physical location for the moduleto be installed in the vehicle. This physical location provides accessto the electrical/signaling interface, provides a particular level ofenvironmental protection, and accommodate a particular size and shape ofadd-on modules.

The electrical/signaling interface may include a standardized connectorto the vehicle's standardized internal communications bus, such asCAN-bus, and a standardized connector to an electrical supply. In somevehicles, the vehicle's communications bus can be a non-electricalstandard, such as a Fiber-optic based system. While such a system maynot be compatible with electrically signaled CAN based systems, thegeneral principle of the extension interface can still apply.

The software interface defines the protocol messages by which theexpansion module interfaces with existing modules in the vehicle.

In one embodiment, the other relevant modules in the vehicle aredesigned to communicate with the expansion module as defined elsewherein the application. The expansion module provides a communications pathto external networks which allows vehicle modules to participate in asmart charging program in a manner similar to that of a vehicle that isinitially equipped with a communications module.

In an embodiment, existing modules in the vehicle have no explicitsupport for smart charging, and all smart charging logic is contained inthe expansion module. As such, the expansion module is solelyresponsible for participating in the smart charging program. Theexpansion module implements the program by sending primitive messages toother subsystems in the vehicle.

FIG. 27 illustrates an embodiment of an extensibility system including acontact plug for a CAN-bus in a vehicle 2710. An expansion moduleprovides standardization of transmitted messages to control charging2720. In addition, a charge controller for control extensibility islocated at the contact plug 2730.

Communications Without Specific Hardware

In many applications, it is beneficial for an electrical load, such asan electric vehicle, to communicate with an electric power supply, suchas a charging station or an electric vehicle service equipment. Suchcommunication can convey information such as device identification,state of battery charge, or power consumption preferences. Thiscommunication can also be utilized to implement the arbitration protocoldescribed herein. The communication is desirable even in situationswhere the two devices in question do not possess hardware designed tofacilitate communication.

For devices to communicate without specific communications hardware,information can be conveyed by modulating the power transfer between theelectrical load (e.g. an electric vehicle) and the electric power supply(electric vehicle service equipment). To facilitate the transmission ofinformation from the electrical load to the electric power supply, anelectric load device can intermittently draw power and/or refrain fromdrawing power. Communications time may be subdivided into seconds. Forexample, each second wherein the load device drew power is interruptedas the binary 1 digit, and each second wherein the load device did notdraw power is interrupted as the binary 0 digit. In a similar manner,the power supply device can communicate with the load device tofacilitate the transmission of information from the electric powersupply to the electric load device. The electric power supply canprovide power for an interval, represented as the binary 1 digit, orrefraining from providing power, represent as the binary 0 digit.

A variety of standard communication protocol techniques may be used toaddress issues such as data reliability and clock drift. Depending onthe accuracy of both sensing equipment in the receiving device andswitching equipment in the transmitting device, the time interval can bevaried. For example, the time interval may be varied to an interval muchlower than one second. Lower intervals would allow a greater amount ofinformation to be transmitted in the same amount of time.

Because the non-powered intervals deprive the load device of electricalpower, the load device requires a supplemental power source to remainfunctional during such intervals. This supplemental power source can bea storage battery, a capacitor, or an alternative primary electricalsource. This system does not interfere with the primary function of thepower circuit, which is power transfer, because all communication may becompleted early in the power connection and power can flow uninterruptedfor the remainder of the connection time.

To address the limitation of communications mediums that prohibit boththe electric vehicle and the electric power source from transmittinginformation simultaneously, a variety of sharing protocols can be used.In one embodiment, the electric power supply and the electric vehicletake turns transmitting information, reversing roles after a fixednumber of bits. In an embodiment, the transmitted messages arestructured as packets with a transmitted size. After the transmission ofa packet, the direction of transmission is reversed.

FIG. 28 illustrates an embodiment of communications without specifichardware including modulating power transfer between an electrical loadassociated with an electric vehicle and a power supply 2810,transmitting information from the electrical load to the power supply2820, and enabling the electrical vehicle to communicate with the powersupply 2830.

Arbitrating Smart Chargepoint With Smart Vehicle

Modern Electric vehicles could benefit in a variety of ways from acentrally controlled smart charging program where a central servercoordinates the charging activities of a large number of vehiclesdistributed over a wide area, such as a city. This coordination isaccomplished by the server communicating directly with a smart chargingmodule located at each vehicle. The smart charging module can be locatedinside the vehicle, either as an original component of the vehicle or anaftermarket accessory. Equipment located inside the vehicle can moderateelectrical load by directly reducing the power consumption of thevehicle.

In one embodiment, the smart charging module will be located in externalequipment responsible for providing electricity to the vehicle. Suchexternal equipment may be electric vehicle service equipment (EVSE).EVSE or charging stations can reduce power consumption by curtailing thepower available to the vehicle.

In the case where both the electric vehicle and the EVSE contain smartcharging modules, a potential problem arises. Because charge managementsystems can be integrated into both vehicles and vehicle charginginfrastructure, each of these systems may initially assume that they arethe only charging intelligence present in a charging session. When asmart car attaches to a smart chargepoint, certain problems arise.Because the two devices are not communicating with each other, thedevices each act as if they have full control of the charge session. Ifthe central smart charging server is not informed that the two devicesrepresent a single vehicle, it will manage the two devicesindependently. The two devices may attempt to charge at different times,resulting in no power flow. Furthermore, both devices may receive stopcharging messages from a utility at the same time, resulting indouble-counting of load reduction.

To address these concerns, electric vehicles and charging equipment, orEVSE, can both implement a charge coordination protocol. This protocolallows the EVSE and the vehicle to determine which of the two entitiesis responsible for communicating with the charge management server andimplementing a smart charging program. The other entity would enter apassive mode, following the direction of the primary entity.

With such a protocol, an electric vehicle can transmit a chargecoordination capabilities message to the chargepoint when the vehicle isconnected. The capabilities message specifies charge coordination modesthat the vehicle supports. The charge equipment can send a chargecoordination mode message specifying the coordination mode. This modemay be selected from the list provided by the vehicle. When the twomessages have been transmitted, the charge equipment and vehiclecommence coordinated charging.

Two coordinated charging modes are initially defined as charge-equipmentswitching charging and vehicle-switching charging. In thecharge-equipment switched charging mode, the electric vehicle stopssmart charging and behaves as a dumb load. The EVSE, or the chargeequipment, sends electricity as it determines while the vehicle does notcommunicate with any external entity for purposes of charge management.As such, the EVSE controls the rate of electricity flow to the vehicleand is responsible for all communication with smart charging server.

In the vehicle-switched charging mode, the EVSE or charging equipmentdoes not engage in smart charging and provide electricity on-demand tothe Vehicle at all times. The electric vehicle controls its rate ofelectricity consumption and is responsible for all communication withthe smart charging server. The electric vehicle performs the physicalregulation of charge level. However, the regulation of charging is basedon commands issued by the charging equipment.

If the vehicle possessed an alternative communications channel, such ascellular, the vehicle stops accepting charge commands from that channel.Charging equipment may monitor the vehicle to determine whether thevehicle had complied with charge directives. The vehicle can fall backto direct control if it is determined that the vehicle Wasnon-compliant.

Additional charging modes may be defined over time. Communicationbetween the electric vehicle and the EVSE could be accomplished viaPower Line Communications (PLC) over the charging cable, or via othermeans, including wireless communications.

FIG. 29 illustrates an embodiment of arbitrating a smart chargepointwith a smart charging module configured to be implemented on vehicleequipment 2910. The module is configured to communicate with the smartcharging program 2920, and to moderate an electric load by reducingpower consumption of the vehicle 2930. In addition, the module isconfigured to communicate with a second smart charging module inexternal charging equipment 2940, and the modules implement a chargecoordination protocol 2950.

CONCLUSION

Although systems and methods have been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described. Rather,the specific features and acts are disclosed as examples ofimplementations of the claimed methods, devices, systems, etc. It willbe understood by those skilled in the art that various changes in formand details may be made therein without departing from the spirit andscope of the invention.

1. A method for managing an electric vehicle charging network, themethod comprising: communicating a first charging behavior from acentral flow controller to a plurality of electric vehicles; controllingpower flow between each of a plurality of charging stations and theircorresponding electric vehicles according to the first chargingbehavior; detecting a communications failure between the central flowcontroller and one or more of the plurality of electric vehicles; andcontrolling, in response to detecting the communications failure, powerflow between (i) one or more of the plurality of charging stationsexperiencing the communications failure and (ii) their correspondingelectric vehicles according to the second charging behavior during theperiod of time of the communications failure, wherein the secondcharging behavior is predictable.
 2. The method of claim 1, wherein thesecond charging behavior comprises: maintaining the first chargingbehavior for a predefined period of time; and transitioning to apredefined autonomous charging strategy after the predefined period oftime.
 3. The method of claim 1, wherein the second charging behaviorcomprises: limiting the power flow to each of the plurality of electricvehicles to a value calculated to allow the plurality of electricvehicles to charge at combined maximum power draw of the electricalcircuit supplying power to the plurality of charging stations.
 4. Themethod of claim 1, wherein the second charging behavior comprises:executing charging behavior state transitions for each of the pluralityof electric vehicles, the charging state behavior state transitionsoccurring at random offset times after the detection of thecommunications failure.
 5. The method of claim 1, wherein the secondcharging behavior comprises: executing charging behavior statetransitions for each of the plurality of electric vehicles, the chargingbehavior state transitions occurring at random offset times after thedetection of the communications failure, wherein electric vehicles ofthe plurality of electric vehicles that are not being charged at thetime of the detected communications failure wait a random amount of timebefore initiating charging, and wherein electric vehicles of theplurality of electric vehicles that are being charged at the time of thedetected communications failure wait a random amount of time beforeterminating charging.
 6. The method of claim 1, wherein the secondcharging behavior comprises: controlling power flow of each of theplurality of electric vehicles detecting the communications failureaccording to a predefined power curve stored in each of the plurality ofelectric vehicles and in the central flow controller; determining, bythe flow controller, appropriate charging behaviors for each of theplurality of electric vehicles that are not experiencing thecommunications failure based on the predefined power curve stored ineach of the plurality of electric vehicles that are experiencing thecommunications failure; and communicating the appropriate chargingbehaviors from the central flow controller to the plurality of electricvehicles that are not experiencing the communications failure.
 7. Themethod of claim 1, wherein the second charging behavior comprises:predicting the connection and disconnection of other of the plurality ofelectric vehicles to and from the plurality of charging stations, andcontrolling power flow based on those predictions.
 8. A computer programproduct for managing an electric vehicle charging network, the productcomprising: a computer usable medium having computer readable programcode embodied in the computer usable medium for causing an applicationprogram to execute on a computer system, the computer readable programcode means comprising: computer readable program code for communicatinga first charging behavior from a central flow controller to a pluralityof electric vehicles; computer readable program code for controllingpower flow between each of a plurality of charging stations and theircorresponding electric vehicles according to the first chargingbehavior; computer readable program code for detecting a communicationsfailure between the central flow controller and the plurality ofelectric vehicles; and computer readable program code for controlling,in response to detecting the communications failure, power flow between(i) one or more of a plurality of charging stations experience thecommunications failure and (ii) their corresponding electric vehiclesaccording to the second charging behavior during the period of time ofthe communications failure, wherein the second charging behavior ispredictable.
 9. The computer program product of claim 8, wherein thecomputer readable program code for controlling power flow according tothe second charging behavior comprises: computer readable program codefor maintaining the first charging behavior for a predefined period oftime; and computer readable program code for transitioning to apredefined autonomous charging strategy after the predefined period oftime.
 10. The computer program product of claim 8, wherein the computerreadable program code for controlling power flow according to the secondcharging behavior comprises: computer readable program code for limitingthe power flow to each of the plurality of electric vehicles to a valuecalculated to allow the plurality of electric vehicles to charge atcombined maximum power draw of the electrical circuit supplying power tothe plurality of charging stations.
 11. The computer program product ofclaim 8, wherein the computer readable program code for controllingpower flow according to the second charging behavior comprises: computerreadable program code for executing charging behavior state transitionsfor each of the plurality of electric vehicles, the charging behaviorstate transitions occurring at random offset times after the detectionof the communications failure.
 12. The computer program product of claim8, wherein the computer readable program code for controlling power flowaccording to the second charging behavior comprises: computer readableprogram code for executing charging behavior state transitions for eachof the plurality of electric vehicles, the charging behavior statetransitions occurring at random offset times after the detection of thecommunications failure, wherein electric vehicles of the plurality ofelectric vehicles that are not being charged at the time of the detectedcommunications failure wait a random amount of time before initiatingcharging, and wherein electric vehicles of the plurality of electricvehicles that are being charged at the time of the detectedcommunications failure wait a random amount of time before terminatingcharging.
 13. The computer program product of claim 8, furthercomprising: computer readable program code for controlling power flow ofeach of the plurality of electric vehicles detecting the communicationsfailure according to a predefined curve stored in each of the pluralityof electric vehicles and in the central flow controller; computerreadable program code for determining appropriate charging behaviors foreach of the plurality of electric vehicles that are not experiencing thecommunications failure based on the predefined power curve stored ineach of the plurality of electric vehicles that are experiencing thecommunications failure; and computer readable program code forcommunicating the appropriate charging behaviors from the central flowcontroller to the plurality of electric vehicles that are notexperiencing the communications failure.
 14. The computer programproduct of claim 8, wherein the computer readable program code forcontrolling power flow according to the second charging behaviorcomprises: computer readable program code for predicting the connectionand disconnection of other of the plurality of electric vehicles to andfrom the plurality of charging stations, and controlling power flowbased on those predictions.
 15. A system for managing an electricvehicle charging network, the system comprising: a central power flowcontroller communicatively coupled to a plurality of electric vehicles,the central power flow controller communicating a first chargingbehavior to the plurality of electric vehicles, each of the plurality ofelectric vehicles including: a memory for storing a plurality ofcharging behaviors from the central flow controller; a processor forcontrolling power flow between its associated electric vehicle and anassociated charging station according to the first charging behavior ofthe plurality of charging behaviors received from the central flowcontroller; and a communication interface for detecting a communicationsfailure between the central flow controller and the electric vehicle,wherein in response to detecting the communications failure, theprocessor controls power flow between (i) the associated chargingstation and (ii) the electric vehicle according to the second chargingbehavior during the period of time of the communications failure, andwherein the second charging behavior is predictable.
 16. The system ofclaim 15, wherein the second charging behavior comprises: maintainingthe first charging behavior for a predefined period of time; andtransitioning to a predefined autonomous charging strategy after thepredefined period of time.
 17. The system of claim 15 wherein the secondcharging behavior comprises: limiting the power flow to each of theplurality of electric vehicles to a value calculated to allow theplurality of electric vehicles to charge at combined maximum power drawof the electrical circuit supplying power to the plurality of chargingstations.
 18. The system of claim 15, wherein the second chargingbehavior comprises: executing charging behavior state transitions foreach of the plurality of electric vehicles, the charging behavior statetransitions occurring at random offset times after the detection of thecommunications failure.
 19. The system of claim 15, wherein the secondcharging behavior comprises: executing charging behavior statetransitions for each of the plurality of electric vehicles, the chargingbehavior state transitions occurring at random offset times after thedetection of the communications failure, wherein electric vehicles ofthe plurality of electric vehicles that are not being charged at thetime of the detected communications failure wait a random amount of timebefore initiating charging, and wherein electric vehicles of theplurality of electric vehicles that are being charged at the time of thedetected communications failure wait a random amount of time beforeterminating charging.
 20. The system of claim 15, wherein the secondcharging behavior includes controlling power flow of each of theplurality of electric vehicles detecting the communications failureaccording to a predefined power curve stored in each of the plurality ofelectric vehicles and in the flow controller, and the flow controllerdetermines appropriate charging behaviors for each of the plurality ofelectric vehicles that are not experiencing the communications failurebased on the predefined power curve stored in each of the plurality ofelectric vehicles that are experiencing the communications failure, andcommunicates the appropriate charging behaviors to the plurality ofelectric vehicles that are not experiencing the communications failure.21. The system of claim 15, wherein the second charging behaviorincludes predicting the connection and disconnection of other of theplurality of electric vehicles to and from the plurality of chargingstations, and controlling power flow based on those predictions.